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3,986 results on '"Martín, Carlos A."'

1. Towards Efficient Modelling of String Dynamics: A Comparison of State Space and Koopman based Deep Learning Methods

Author

Diaz, Rodrigo, Martin, Carlos De La Vega, and Sandler, Mark

Subjects
Computer Science - Sound, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing, Physics - Computational Physics
Abstract

This paper presents an examination of State Space Models (SSM) and Koopman-based deep learning methods for modelling the dynamics of both linear and non-linear stiff strings. Through experiments with datasets generated under different initial conditions and sample rates, we assess the capacity of these models to accurately model the complex behaviours observed in string dynamics. Our findings indicate that our proposed Koopman-based model performs as well as or better than other existing approaches in non-linear cases for long-sequence modelling. We inform the design of these architectures with the structure of the problems at hand. Although challenges remain in extending model predictions beyond the training horizon (i.e., extrapolation), the focus of our investigation lies in the models' ability to generalise across different initial conditions within the training time interval. This research contributes insights into the physical modelling of dynamical systems (in particular those addressing musical acoustics) by offering a comparative overview of these and previous methods and introducing innovative strategies for model improvement. Our results highlight the efficacy of these models in simulating non-linear dynamics and emphasise their wide-ranging applicability in accurately modelling dynamical systems over extended sequences., Comment: Accepted to DAFx2024

Published
2024

2. Joint-perturbation simultaneous pseudo-gradient

Author

Martin, Carlos and Sandholm, Tuomas

Subjects
Computer Science - Computer Science and Game Theory, Computer Science - Multiagent Systems
Abstract

We study the problem of computing an approximate Nash equilibrium of a game whose strategy space is continuous without access to gradients of the utility function. Such games arise, for example, when players' strategies are represented by the parameters of a neural network. Lack of access to gradients is common in reinforcement learning settings, where the environment is treated as a black box, as well as equilibrium finding in mechanisms such as auctions, where the mechanism's payoffs are discontinuous in the players' actions. To tackle this problem, we turn to zeroth-order optimization techniques that combine pseudo-gradients with equilibrium-finding dynamics. Specifically, we introduce a new technique that requires a number of utility function evaluations per iteration that is constant rather than linear in the number of players. It achieves this by performing a single joint perturbation on all players' strategies, rather than perturbing each one individually. This yields a dramatic improvement for many-player games, especially when the utility function is expensive to compute in terms of wall time, memory, money, or other resources. We evaluate our approach on various games, including auctions, which have important real-world applications. Our approach yields a significant reduction in the run time required to reach an approximate Nash equilibrium.

Published
2024

3. Modelling the three-dimensional, diagnostic anisotropy field of an ice rise

Author

Henry, A. Clara J., Martín, Carlos, and Drews, Reinhard

Subjects
Physics - Fluid Dynamics, Physics - Geophysics
Abstract

Polar ice develops anisotropic crystal orientation fabrics under deformation, yet ice is most often modelled as an isotropic fluid. We present three-dimensional simulations of the crystal orientation fabric of Derwael Ice Rise including the surrounding ice shelf using a crystal orientation tensor evolution equation corresponding to a fixed velocity field. We use a semi-Lagrangian numerical method that constrains the degree of crystal orientation evolution to solve the equations in complex flow areas. We perform four simulations based on previous studies, altering the rate of evolution of the crystal anisotropy and its dependence on a combination of the strain rate and deviatoric stress tensors. We provide a framework for comparison with radar observations of the anisotropy field, outlining areas where the assumption of one vertical eigenvector may not hold and provide resulting errors in measured eigenvalues. We recognise the areas of high horizontal divergence at the ends of the flow divide as important areas to make comparisons with observations. Here, poorly constrained model parameters result in the largest difference in fabric type. These results are important in the planning of future campaigns for gathering data to constrain model parameters and as a link between observations and computationally-efficient, simplified models of anisotropy.

Published
2024

4. AlphaZeroES: Direct score maximization outperforms planning loss minimization

Author

Martin, Carlos and Sandholm, Tuomas

Subjects
Computer Science - Artificial Intelligence
Abstract

Planning at execution time has been shown to dramatically improve performance for agents in both single-agent and multi-agent settings. A well-known family of approaches to planning at execution time are AlphaZero and its variants, which use Monte Carlo Tree Search together with a neural network that guides the search by predicting state values and action probabilities. AlphaZero trains these networks by minimizing a planning loss that makes the value prediction match the episode return, and the policy prediction at the root of the search tree match the output of the full tree expansion. AlphaZero has been applied to both single-agent environments (such as Sokoban) and multi-agent environments (such as chess and Go) with great success. In this paper, we explore an intriguing question: In single-agent environments, can we outperform AlphaZero by directly maximizing the episode score instead of minimizing this planning loss, while leaving the MCTS algorithm and neural architecture unchanged? To directly maximize the episode score, we use evolution strategies, a family of algorithms for zeroth-order blackbox optimization. Our experiments indicate that, across multiple environments, directly maximizing the episode score outperforms minimizing the planning loss., Comment: arXiv admin note: text overlap with arXiv:2308.08693

Published
2024

5. Simultaneous incremental support adjustment and metagame solving: An equilibrium-finding framework for continuous-action games

Author

Martin, Carlos and Sandholm, Tuomas

Subjects
Computer Science - Computer Science and Game Theory
Abstract

We present a framework for computing approximate mixed-strategy Nash equilibria of continuous-action games. It is a modification of the traditional double oracle algorithm, extended to multiple players and continuous action spaces. Unlike prior methods, it maintains fixed-cardinality pure strategy sets for each player. Thus, unlike prior methods, only a constant amount of memory is necessary. Furthermore, it does not require exact metagame solving on each iteration, which can be computationally expensive for large metagames. Moreover, it does not require global best-response computation on each iteration, which can be computationally expensive or even intractable for high-dimensional action spaces and general games. Our method incrementally reduces the exploitability of the strategy profile in the finite metagame, pushing it toward Nash equilibrium. Simultaneously, it incrementally improves the pure strategies that best respond to this strategy profile in the full game. We evaluate our method on various continuous-action games, showing that it obtains approximate mixed-strategy Nash equilibria with low exploitability., Comment: arXiv admin note: text overlap with arXiv:2301.08830

Published
2024

6. AERIAL-CORE: AI-Powered Aerial Robots for Inspection and Maintenance of Electrical Power Infrastructures

Author

Ollero, Anibal, Suarez, Alejandro, Papaioannidis, Christos, Pitas, Ioannis, Marredo, Juan M., Duong, Viet, Ebeid, Emad, Kratky, Vit, Saska, Martin, Hanoune, Chloe, Afifi, Amr, Franchi, Antonio, Vourtsis, Charalampos, Floreano, Dario, Vasiljevic, Goran, Bogdan, Stjepan, Caballero, Alvaro, Ruggiero, Fabio, Lippiello, Vincenzo, Matilla, Carlos, Cioffi, Giovanni, Scaramuzza, Davide, Martinez-de-Dios, Jose R., Arrue, Begona C., Martin, Carlos, Zurad, Krzysztof, Gaitan, Carlos, Rodriguez, Jacob, Munoz, Antonio, and Viguria, Antidio

Subjects
Computer Science - Robotics
Abstract

Large-scale infrastructures are prone to deterioration due to age, environmental influences, and heavy usage. Ensuring their safety through regular inspections and maintenance is crucial to prevent incidents that can significantly affect public safety and the environment. This is especially pertinent in the context of electrical power networks, which, while essential for energy provision, can also be sources of forest fires. Intelligent drones have the potential to revolutionize inspection and maintenance, eliminating the risks for human operators, increasing productivity, reducing inspection time, and improving data collection quality. However, most of the current methods and technologies in aerial robotics have been trialed primarily in indoor testbeds or outdoor settings under strictly controlled conditions, always within the line of sight of human operators. Additionally, these methods and technologies have typically been evaluated in isolation, lacking comprehensive integration. This paper introduces the first autonomous system that combines various innovative aerial robots. This system is designed for extended-range inspections beyond the visual line of sight, features aerial manipulators for maintenance tasks, and includes support mechanisms for human operators working at elevated heights. The paper further discusses the successful validation of this system on numerous electrical power lines, with aerial robots executing flights over 10 kilometers away from their ground control stations.

Published
2024

9. A Change of Paradigm in the Management of Acute Psychiatric Episodes? A Retrospective Cohort Study on Trajectories of Use of Clinical Resources After the Implementation of Intensive Home-Treatment

Author

Martín-Blanco, Ana, González-Fernández, Alba, Farré, Adriana, Sagué-Vilavella, Maria, Vieira, Sara, Giménez, David, Alvaro, Patricia, Isern, Clara, Torres, Cristina, de la Cruz, Vicente, Martín, Carlos, Moll, Núria, and Portella, Maria Jesús

Published
2024
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10. State of the Art Report: Verified Computation

Author

Woodcock, Jim, Andersen, Mikkel Schmidt, Aranha, Diego F., Hallerstede, Stefan, Hansen, Simon Thrane, Jakobsen, Nikolaj Kuhne, Kulik, Tomas, Larsen, Peter Gorm, Macedo, Hugo Daniel, Martin, Carlos Ignacio Isasa, and Norrild, Victor Alexander Mtsimbe

Subjects
Computer Science - Cryptography and Security
Abstract

This report describes the state of the art in verifiable computation. The problem being solved is the following: The Verifiable Computation Problem (Verifiable Computing Problem) Suppose we have two computing agents. The first agent is the verifier, and the second agent is the prover. The verifier wants the prover to perform a computation. The verifier sends a description of the computation to the prover. Once the prover has completed the task, the prover returns the output to the verifier. The output will contain proof. The verifier can use this proof to check if the prover computed the output correctly. The check is not required to verify the algorithm used in the computation. Instead, it is a check that the prover computed the output using the computation specified by the verifier. The effort required for the check should be much less than that required to perform the computation. This state-of-the-art report surveys 128 papers from the literature comprising more than 4,000 pages. Other papers and books were surveyed but were omitted. The papers surveyed were overwhelmingly mathematical. We have summarised the major concepts that form the foundations for verifiable computation. The report contains two main sections. The first, larger section covers the theoretical foundations for probabilistically checkable and zero-knowledge proofs. The second section contains a description of the current practice in verifiable computation. Two further reports will cover (i) military applications of verifiable computation and (ii) a collection of technical demonstrators. The first of these is intended to be read by those who want to know what applications are enabled by the current state of the art in verifiable computation. The second is for those who want to see practical tools and conduct experiments themselves., Comment: 54 pages

Published
2023

11. AI planning in the imagination: High-level planning on learned abstract search spaces

Author

Martin, Carlos and Sandholm, Tuomas

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Search and planning algorithms have been a cornerstone of artificial intelligence since the field's inception. Giving reinforcement learning agents the ability to plan during execution time has resulted in significant performance improvements in various domains. However, in real-world environments, the model with respect to which the agent plans has been constrained to be grounded in the real environment itself, as opposed to a more abstract model which allows for planning over compound actions and behaviors. We propose a new method, called PiZero, that gives an agent the ability to plan in an abstract search space that the agent learns during training, which is completely decoupled from the real environment. Unlike prior approaches, this enables the agent to perform high-level planning at arbitrary timescales and reason in terms of compound or temporally-extended actions, which can be useful in environments where large numbers of base-level micro-actions are needed to perform relevant macro-actions. In addition, our method is more general than comparable prior methods because it seamlessly handles settings with continuous action spaces, combinatorial action spaces, and partial observability. We evaluate our method on multiple domains, including the traveling salesman problem, Sokoban, 2048, the facility location problem, and Pacman. Experimentally, it outperforms comparable prior methods without assuming access to an environment simulator at execution time.

Published
2023

12. ApproxED: Approximate exploitability descent via learned best responses

Author

Martin, Carlos and Sandholm, Tuomas

Subjects
Computer Science - Computer Science and Game Theory, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Multiagent Systems
Abstract

There has been substantial progress on finding game-theoretic equilibria. Most of that work has focused on games with finite, discrete action spaces. However, many games involving space, time, money, and other fine-grained quantities have continuous action spaces (or are best modeled as having such). We study the problem of finding an approximate Nash equilibrium of games with continuous action sets. The standard measure of closeness to Nash equilibrium is exploitability, which measures how much players can benefit from unilaterally changing their strategy. We propose two new methods that minimize an approximation of exploitability with respect to the strategy profile. The first method uses a learned best-response function, which takes the current strategy profile as input and outputs candidate best responses for each player. The strategy profile and best-response functions are trained simultaneously, with the former trying to minimize exploitability while the latter tries to maximize it. The second method maintains an ensemble of candidate best responses for each player. In each iteration, the best-performing elements of each ensemble are used to update the current strategy profile. The strategy profile and ensembles are simultaneously trained to minimize and maximize the approximate exploitability, respectively. We evaluate our methods on various continuous games and GAN training, showing that they outperform prior methods.

Published
2023

15. Finding mixed-strategy equilibria of continuous-action games without gradients using randomized policy networks

Author

Martin, Carlos and Sandholm, Tuomas

Subjects
Computer Science - Computer Science and Game Theory, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Multiagent Systems
Abstract

We study the problem of computing an approximate Nash equilibrium of continuous-action game without access to gradients. Such game access is common in reinforcement learning settings, where the environment is typically treated as a black box. To tackle this problem, we apply zeroth-order optimization techniques that combine smoothed gradient estimators with equilibrium-finding dynamics. We model players' strategies using artificial neural networks. In particular, we use randomized policy networks to model mixed strategies. These take noise in addition to an observation as input and can flexibly represent arbitrary observation-dependent, continuous-action distributions. Being able to model such mixed strategies is crucial for tackling continuous-action games that lack pure-strategy equilibria. We evaluate the performance of our method using an approximation of the Nash convergence metric from game theory, which measures how much players can benefit from unilaterally changing their strategy. We apply our method to continuous Colonel Blotto games, single-item and multi-item auctions, and a visibility game. The experiments show that our method can quickly find high-quality approximate equilibria. Furthermore, they show that the dimensionality of the input noise is crucial for performance. To our knowledge, this paper is the first to solve general continuous-action games with unrestricted mixed strategies and without any gradient information.

Published
2022
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17. Wound bed preparation 2024: Delphi consensus on foot ulcer management in resource-limited settings

Author

Smart, Hiske, Sibbald, R Gary, Goodman, Laurie, Elizabeth, A Ayello, Jaimangal, Reneeka, Gregory, John H, Akita, Sadanori, Alavi, Afsaneh, Armstrong, David G, Arputhanathan, Helen, Bruwer, Febe, Caul, Jeremy, Chan, Beverley, Cronje, Frans, Dofitas, Belen, Hamed, Jassin, Harley, Catherine, Heil, Jolene, Hill, Mary, Jahnke, Devon, Kalina, Dale, Kodange, Chaitanya, Kotru, Bharat, Kozody, Laura Lee, Landis, Stephan, LeBlanc, Kimberly, MacDonald, Mary, Mark, Tobi, Martin, Carlos, Mayer, Dieter, Murphy, Christine, Nair, Harikrishna, Orellana, Cesar, Ostrow, Brian, Queen, Douglas, Rainville, Patrick, Rajhathy, Erin, Schultz, Gregory, Somayaji, Ranjani, Stacey, Michael C, Tariq, Gulnaz, Weir, Gregory, Whiteside, Catharine, Yifter, Helen, and Zacharias, Ramesh

Published
2024

21. Efficacy and safety of biological treatment for inflammatory bowel disease in elderly patients: Results from a GETECCU cohort

Author

Suárez Ferrer, Cristina, Mesonero Gismero, Francisco, Caballol, Berta, Ballester, Maria Pilar, Bastón Rey, Iria, Castaño García, Andrés, Miranda Bautista, Jose, Saiz Chumillas, Rosa, Benitez, Jose Manuel, Sanchez-Delgado, Laura, López-García, Alicia, Rubin de Celix, Cristina, Alonso Abreu, Inmaculada, Melcarne, Luigi, Plaza Santos, Rocío, Marques-Camí, Miquel, Caballero Mateos, Antonio, Gómez Díez, César, Calafat, Margalida, Galan, Horacio Alonso, Vega Vilaamil, Pablo, Castro Senosiain, Beatriz, Guerro Moya, Andrea, Rodriguez Diaz, Carmen Yolanda, Spicakova, Katerina, Manceñido Marcos, Noemi, Molina, Gema, de Castro Parga, Luisa, Rodriguez Angulo, Andres, Cuevas del Campo, Lidia, Rodriguez Grau, Maria del Carmen, Ramirez, Fernando, Gomez Pastrana, Barbara, Gonzalez Partida, Irene, Botella Mateu, Belen, Peña Gonzalez, Elena, Iyo, Eduardo, Elosua Gonzalez, Alfonso, Sainz Arnau, Empar, Hernandez Villalba, Luis, Perez Galindo, Pablo, Torrealba Medina, Leyanira, Monsalve Alonso, Sara, Olmos Perez, Jose Antonio, Dueñas Sadornil, Carmen, Garcia Ramirez, Laura, Martín-Arranz, María Dolores, López Sanroman, Antonio, Fernández, Agnès, Merino Murgui, Victor, Calviño Suárez, Cristina, Flórez-Diez, Pablo, Lobato Matilla, María Elena, Sicilia, Beatriz, Soto Escribano, Pilar, Maroto Martin, Carlos, Mañosa, Míriam, and Barreiro-De Acosta, Manuel

Published
2024
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26. Tecnología de Internet de las Cosas en el monitoreo de cultivos agrícolas

Author

Martín Carlos Abad Alay, María Alejandra Méndez García, and Orlando Erazo Moreta

Subjects
procesamiento de datos, productos agrícolas, sistema agrario, vigilancia, Computer software, QA76.75-76.765
Abstract

El Internet de las Cosas (IoT) desempeña un papel importante en la agricultura porque proporciona beneficios para el desarrollo de cultivos y mejora de producción. Como existen diversos artículos que muestran su utilidad, la finalidad de este trabajo es analizarlos sistemáticamente para extraer datos sobre sistemas IoT enfocados en monitorizar cultivos agrícolas. Como parte del protocolo de revisión se plantearon cuatro preguntas direccionadas a conocer más sobre la manera en que se realiza el monitoreo, los componentes empleados, las funcionalidades y los datos recolectados. Utilizando cuatro de las bases de datos populares del área, se seleccionaron 41 artículos. De la extracción de datos se pudo conocer la utilización de dispositivos IoT con cierta preferencia hacia las aplicaciones móviles y una tendencia a emplear componentes como: ESP8266, YL-69, DTH-1 y Arduino. Además, entre las funcionalidades identificadas están el monitoreo del suelo, del crecimiento y rendimiento del cultivo, de la invasión de animales, el riego automático, entre otras. Por último, se encontraron varias decenas de tipos de datos que recolectan los dispositivos como parámetros ambientales y características del suelo. Todos estos datos ayudan en la caracterización de los sistemas IoT de interés y pueden servir de base para desarrollar otros.

Published
2023
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28. Generation of human alveolar epithelial type I cells from pluripotent stem cells

Author

Burgess, Claire L., Huang, Jessie, Bawa, Pushpinder S., Alysandratos, Konstantinos-Dionysios, Minakin, Kasey, Ayers, Lauren J., Morley, Michael P., Babu, Apoorva, Villacorta-Martin, Carlos, Yampolskaya, Maria, Hinds, Anne, Thapa, Bibek R., Wang, Feiya, Matschulat, Adeline, Mehta, Pankaj, Morrisey, Edward E., Varelas, Xaralabos, and Kotton, Darrell N.

Published
2024
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29. Four-year overall survival update from the phase III HIMALAYA study of tremelimumab plus durvalumab in unresectable hepatocellular carcinoma

Author

Azevedo, Sergio, Braghiroli, Maria Ignez, Girotto, Gustavo, Bragagnoli, Arinilda, Branco, Ricardo, Faccio, Adilson, Moretto, Andrea, Skare, Nils, Dutra, Jamille, Viola, Luciana, Vianna, Karina, Meton, Fernando, Sette, Claudia, Faulhaber, Amanda, Tam, Vincent C., Couture, Felix, Biagi, Jim, Castel, Helene, Mulder, Karen, Ko, Yoo-Joung, Zbuk, Kevin, Welch, Stephen, Beaudoin, Annie, Heurgué, Alexandra, Assenat, Eric, Archambeaud, Isabelle, Tougeron, David, Peron, Jean-Marie, Gilabert, Marine, Bronowicki, Jean-Pierre, Cattan, Stephane, Blanc, Jean-Frederic, Bouattour, Mohamed, Phelip, Jean-Marc, Boige, Valerie, Michel, Pierre, Frin, Anne-Claire, De Toni, Enrico N., Berres, Marie-Luise, Vogel, Arndt, Berg, Thomas, Ettrich, Thomas, Waldschmidt, Dirk, Wedemeyer, Hans Heinrich, Worns, Marcus-Alexander, Bitzer, Michael, Weiss, Karl-Heinz, Lau, George, Chan, Stephen L., Yau, Thomas, Tai, Yin Ping, Lee, Ann Shing, Thungappa, Satheesh Chiradoni, N, Lokesh K., Sureshchand Ostwal, Vikas, Ashok, Kattimani Kiran, Mittal, Sushant, Goyal, Hari, Srinivasan, Sankar, Biswas, Ghanashyam, Mohan, Mallavarapu, Limaye, Sewanti, Asarawala, Nirav, Rimassa, Lorenza, Falcone, Alfredo, Gianni, Luca, Gasbarrini, Antonio, Daniele, Bruno, Avallone, Antonio, Paolo Frassineti, Giovanni Luca, Roila, Fausto, Kudo, Masatoshi, Kawaoka, Tomokazu, Morimoto, Manabu, Takikawa, Yasuhiro, Kato, Naoya, Yamashita, Tatsuya, Osaki, Yukio, Motomura, Kenta, Tateishi, Ryosuke, Ohkawa, Kazuyoshi, Wada, Yoshiyuki, Onishi, Hideki, Sasahira, Naoki, Inaba, Yoshitaka, Kurosaki, Masayuki, Tsuji, Kunihiko, Takei, Yoshiyuki, Aramaki, Takeshi, Hagihara, Atsushi, Furuse, Junji, Kioka, Kiyohide, Koga, Hironori, Sasaki, Yutaka, Numata, Kazushi, Tada, Toshifumi, Kawaguchi, Yasunori, Nadano, Seijin, Vasilyev, Alexander, Breder, Valery, Lipatov, Oleg, Dvorkin, Mikhail, Zarubenkov, Oleg, Kutukova, Svetlana, Ponomarev, Roman, Shostka, Kirill, Alyasova, Anna, Topuzov, Eldar, Severtsev, Alexey, Petrov, Yuryi, Erygin, Dmitriy, Berdov, Boris, Kang, Yoon-Koo, Tak, Won-Young, Park, Joong-Won, Lim, Ho Yeong, Heo, Jeong, Kim, Jee Hyun, Kim, Tae-You, Choi, Hye Jin, Varela, María, Reig Monzon, María Elisa, Sangro, Bruno, Martin, Carlos Gómez, Ponce, Carmen Guillén, López, Carlos, Cheng, Ann-Lii, Chao, Yee, Feng, Yin-Hsun, Jeng, Long-Bin, Hung, Chao-Hung, Hou, Ming-Mo, Wang Tsang-En Wang, Jing-Houng, Yen, Chia-Jui, Sukeepaisarnjaroen, Wattana, Sunpaweravong, Patrapim, Charoentum, Chaiyut, Tanasanvimon, Suebpong, Sirachainan, Ekaphop, Ungtrakul, Teerapat, Prasongsook, Naiyarat, Maneenil, Kunlatida, Jitpewngarm, Wittawat, Ostapenko, Yurii, Skoryi, Denys, Bondarenko, Igor, Shparyk, Yaroslav, Trukhin, Dmytro, Hotko, Yevhen, Ursol, Grygorii, Kryzhanivska, Anna, Abou-Alfa, Ghassan K., Mody, Kabir, Dayyani, Farshid, Al-Rajabi, Raed, Yarchoan, Mark, Gandhi, Sunil, Crysler, Oxana, He, Aiwu Ruth, Reeves, James, Bahary, Nathan, Mahipal, Amit, Kelley, Robin Kate, Dasgupta, Anirudha, Rowe, Julie, Thota, Ramya, Beg, Muhammad, Morse, Michael, Choi, Sung-hee, Crocenzi, Todd, Somer, Bradley, Abrams, Thomas, Denlinger, Crystal, Zhang, Yue, Sharma, Nisha, Dao, Tu V., Thinh, Nguyen Tien, Tuyet Phuong, Le Thi, Sangro, B., Chan, S.L., Kelley, R.K., Lau, G., Kudo, M., Sukeepaisarnjaroen, W., Yarchoan, M., De Toni, E.N., Furuse, J., Kang, Y.K., Galle, P.R., Rimassa, L., Heurgué, A., Tam, V.C., Van Dao, T., Thungappa, S.C., Breder, V., Ostapenko, Y., Reig, M., Makowsky, M., Paskow, M.J., Gupta, C., Kurland, J.F., Negro, A., and Abou-Alfa, G.K.

Published
2024
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36. Efficient exploration of zero-sum stochastic games

Author

Martin, Carlos and Sandholm, Tuomas

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computer Science and Game Theory, Computer Science - Machine Learning, Computer Science - Multiagent Systems, Electrical Engineering and Systems Science - Systems and Control
Abstract

We investigate the increasingly important and common game-solving setting where we do not have an explicit description of the game but only oracle access to it through gameplay, such as in financial or military simulations and computer games. During a limited-duration learning phase, the algorithm can control the actions of both players in order to try to learn the game and how to play it well. After that, the algorithm has to produce a strategy that has low exploitability. Our motivation is to quickly learn strategies that have low exploitability in situations where evaluating the payoffs of a queried strategy profile is costly. For the stochastic game setting, we propose using the distribution of state-action value functions induced by a belief distribution over possible environments. We compare the performance of various exploration strategies for this task, including generalizations of Thompson sampling and Bayes-UCB to this new setting. These two consistently outperform other strategies.

Published
2020

37. Intravenous administration of BCG in mice promotes natural killer and T cell-mediated antitumor immunity in the lung

Author

Moreo, Eduardo, Jarit-Cabanillas, Aitor, Robles-Vera, Iñaki, Uranga, Santiago, Guerrero, Claudia, Gómez, Ana Belén, Mata-Martínez, Pablo, Minute, Luna, Araujo-Voces, Miguel, Felgueres, María José, Esteso, Gloria, Uranga-Murillo, Iratxe, Arias, Maykel, Pardo, Julián, Martín, Carlos, Valés-Gómez, Mar, del Fresno, Carlos, Sancho, David, and Aguiló, Nacho

Published
2023
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39. De novo hematopoiesis from the fetal lung

Author

Yeung, Anthony K., Villacorta-Martin, Carlos, Lindstrom-Vautrin, Jonathan, Belkina, Anna C., Vanuytsel, Kim, Dowrey, Todd W., Ysasi, Alexandra B., Bawa, Pushpinder, Wang, Feiya, Vrbanac, Vladimir, Mostoslavsky, Gustavo, Balazs, Alejandro B., and Murphy, George J.

Published
2023
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40. Atezolizumab plus bevacizumab versus active surveillance in patients with resected or ablated high-risk hepatocellular carcinoma (IMbrave050): a randomised, open-label, multicentre, phase 3 trial

Author

Thompson, Alexander, Danta, Mark, Poursoltan, Pirooz, Kiberu, Andrew, Chittajallu, Renuka, Sood, Siddarth, Stauber, Rudolf, Pinter, Matthias, Peck-Radosavljevic, Markus, Decaestecker, Jochen, Cuyle, Pieter-Jan, Verset, Gontran, Van Vlierberghe, Hans, De Azevedo, Sergio, Andrade, Livia, Cunha Júnior, Ademar, Faria, Luiza, Yen, Cheng Tzu, Colli, Leandro, Asselah, Jamil, Kavan, Petr, Marquez, Vladimir, Brahmania, Mayur, Li, Qiang, Xing, Baocai, Guo, Yabing, Chen, Zhendong, Zhao, Haitao, Peng, Tao, Wang, Liming, Wang, Lu, Liu, Hongming, Wu, Feixiang, Qin, Lunxiu, Zheng, Qichang, Ying, Jieer, Li, Haitao, Wen, Tianfu, Qin, Shukui, Wen, Xiaoyu, Liu, Yunpeng, Chen, Minshan, Wang, Boqing, Bai, Yuxian, He, Yifu, Zhao, Hong, Zhou, Dong, Dai, Chaoliu, Teng, Gaojun, Cui, Shuzhong, Gao, Yi, Zhang, Xizhi, Lu, Zheng, Yin, Tao, Ding, Youming, Jia, Weidong, Xia, Yongxiang, Sun, Beicheng, Xia, Qiang, Yuan, Yufeng, Sun, Huichuan, Shi, Xuetao, Guzmán, Adrián, Corrales, Luis, Kral, Zdenek, Priester, Peter, Kubala, Eugen, Blanc, Jean Frederic, Bourliere, Marc, Peron, Jean Marie, Borg, Christophe, Bronowicki, Jean-Pierre, Ganne, Nathalie, Decaens, Thomas, Uguen, Thomas, Heurgue, Alexandra, Trojan, Joerg, Gonzalez-Carmona, Maria Angeles, Roderburg, Christoph, Ettrich, Thomas, Schotten, Clemens, Kandulski, Arne, Yau, Thomas, Chan, Lam, Scartozzi, Mario, Masi, Gianluca, Fanello, Silvia, Battezzati, Pier Maria, Leonardi, Francesco, Ghidini, Michele, Numata, Kazushi, Morimoto, Manabu, Hidaka, Hisashi, Tsuchiya, Kaoru, Yamashita, Tatsuya, Kato, Naoya, Kudo, Masatoshi, Hagihara, Atsushi, Koga, Hironori, Arakawa, Tomohiro, Nakamura, Ikuo, Kawamura, Yusuke, Kawaoka, Tomokazu, Shimada, Mitsuo, Hasegawa, Kiyoshi, Marusawa, Hiroyuki, Nakamura, Shinchiro, Hiraoka, Atsushi, Hayashi, Hiromitsu, Takeda, Shin, Lee, Han Chu, Paik, Seung Woon, Kim, Do Young, Lee, Jung Il, Jeong, Sook-Hyang, Kim, Won, Tak, Won Young, Heo, Jeong, Kim, Hyeyeong, Chon, Hong Jae, Cheong, Jaeyoun, Yoon, Seung Kew, Yoon, Jung-Hwan, Villalobos, Ricardo, Martinez Rodriguez, Jorge Luis, Oyervides Juarez, Victor, Hernández, Carlos Alberto, Klumpen, Heinz-Josef, de Vos-Geelen, Judith, Gane, Edward, Montenegro, Paola, Torres Mattos, Cesar, Janczewska, Ewa, Kawecki, Maciej, Nowakowska-Zajdel, Ewa, Fedenko, Alexander, Granov, Dmitrii, Alyasova, Anna, Sekacheva, Marina, Ledin, Evgeny, Samol, Jens, Toh, Han Chong, Calvo Campos, Mariona, Gomez Martin, Carlos, Lopez Lopez, Carlos, Muñoz Martin, Andres Jesus, Calleja Panero, Jose Luis, Montero Alvarez, Jose Luis, Reig Monzón, Maria, Delgado Mingorance, Ignacio, Minguez Rosique, Beatriz, Cheng, Ann Lii, Huang, Yi-Hsiang, Lin, Shi-Ming, Huang, Jee-Fu, Yu, Ming-Lung, Su, Wei-Wen, Korphaisarn, Krittiya, Maneenil, Kunlatida, Samdaengpan, Chayanee, Tharavichitkul, Ekkapong, Ozguroglu, Mustafa, Kose, Fatih, Harputluoglu, Hakan, Buchschacher, Gary, Thuluvath, Paul, Xiong, Henry, Patel, Mital, Gold, Philip, Li, Daneng, Brooks, Gabriel, Masood, Ashiq, Patel, Reema, George, Ben, Salgia, Reena, Manji, Gulam, Crow, Mary, Kaseb, Ahmed, Dugan, Matthew, Kadakia, Kunal, Kardosh, Adel, Gibbs, John, Shah, Ashesh, Burris III, Howard, Hsiehchen, David, Cheng, Ann-Lii, Kaseb, Ahmed O, Yopp, Adam C, Zhou, Jian, Nakamura, Shinichiro, Cha, Edward, Hack, Stephen P, Lian, Qinshu, Ma, Ning, Spahn, Jessica H, Wang, Yulei, Wu, Chun, and Chow, Pierce K H

Published
2023
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45. Methodology for Building Virtual Reality Mobile Applications for Blind People on Advanced Visits to Unknown Interior Spaces

Author

Guerrón Paredes, Nancy Enriqueta, Cobo, Antonio, Martín, Carlos, and Serrano, José Javier

Abstract

Virtual reality applications for blind people in smartphones were used to make virtual visits in advance to unknown spaces; these need to include a set of cognitive and sensitive interfaces that allow users to use their other sensory capabilities to understand information about their environment and facilitate the interaction with the application, so that the user can make a mental representation of the unknown space. Some strategies were designed to provide continuous and clear information to the user, so that he can perform exploration activities within a virtual environment generated from a real environment with the help of nineteen blind people and five visually impaired people who participated in the development and tests carried out into six workshops, during twenty-four months. During each workshop took logs about the activities that the user did for the recognized and location of objects and structures indoors. This information was stored in a database to be analyzed and interpreted in order to make subsequent modifications to the application, until achieving a tool that is sufficiently useful, safe and accepted for the user. The last applications were built with voice patterns, beeps, vibrations and gestures called sensitive interfaces, and also with a cognitive interface called "Focus of attention" based on proximity and remote exploration. There was a thirty-eight percent of improvement when the participants chose to remote explore the virtual environment with regard to proximity exploration, also there was preference to be warned with low to medium frequency beeps, a fast reproduction of the voice to receive information on objects and structures and simple gestures for the interaction with Smartphone. In the last experience, we used a structure sensor coupled to the Smartphone for user tracking, and bone conduction headphones to reproduce spatial sounds; they said it was pleasing to hear 3D sounds with personalized response in bone earphones, for locating objects inside the test scenario; there was a twenty-one percent of improvement with the participants using beeps instead of vocals or musical instruments. [For the complete proceedings, see ED590271.]

Published
2018

46. Camrelizumab plus rivoceranib versus sorafenib as first-line therapy for unresectable hepatocellular carcinoma (CARES-310): a randomised, open-label, international phase 3 study

Author

Qin, Shukui, Chan, Stephen L, Cheng, Ann-Lii, Kaseb, Ahmed, Vogel, Arndt, Gu, Shanzhi, Bai, Yuxian, Ren, Zhenggang, Lin, Xiaoyan, Chen, Zhendong, Jia, Weidong, Jin, Yongdong, Guo, Yabing, Hu, Xiaohua, Meng, Zhiqiang, Liang, Jun, Cheng, Ying, Xiong, Jianping, Ren, Hong, Yang, Fang, Li, Wei, Chen, Yajin, Zeng, Yong, Sultanbaev, Alexander, Pazgan-Simon, Monika, Pisetska, Margaryta, Melisi, Davide, Ponomarenko, Dmitriy, Osypchuk, Yurii, Sinielnikov, Ivan, Yang, Tsai-Sheng, Liang, Xiao, Chen, Chunxia, Wang, Linna, Zhang, Mingxiang, Xu, Li, Yuan, Xianglin, Li, Da, Ying, Jierer, Zhang, Jingdong, Zhang, Tao, Gu, Kangsheng, He, Yifu, Hao, Ping, Jiang, Da, Zhang, Shu, Xing, Baocai, Zhang, Baihong, Wang, Dong, Zhai, Xiaofeng, Liang, Houjie, Cybulska-Stopa, Bozena, Dvorkin, Mikhail, Stroyakovskiy, Daniil, Nechaeva, Marina, Yen, Chia-Jui, Su, Wei-Wen, Chen, Yen-Hao, Bondarenko, Igor, Yang, Lin, Fang, Weijia, Gomez-Martin, Carlos, Ryu, Min-Hee, Kim, Han-Sang, Kim, Jee-Hyun, Zarubenkov, Oleg, Orlova, Rashida, Poddubskaya, Elena, Fadeeva, Natalia, Makarova, Yulia, Chao, Yee, Hung, Chao-Hung, Neffa, Maryna, Vynnychenko, Oleksandr, Burgoyne, Adam, Hao, Chunyi, Mohr, Raphael U, Diaz-Beveridge, Roberto, Feliu-Batlle, Jaime, Cubillo-Gracian, Antonio, Lee, Ann-Shing, Daniele, Bruno, Antonuzzo, Lorenzo, Sangiovanni, Angelo, Gasbarrini, Antonio, Scartozzi, Mario, Ahn, Mi Sun, Oh, Sung-Yong, Orlov, Sergey, Harputluoglu, Hakan, Oksuzoglu, Berna, Hsu, Chiun, Rau, Kun-Ming, Krechkovskyi, Oleksandr, Yareshko, Vladimir, Xiong, Henry, Lee, Fa-Chyi, Jiang, Yixing, Gabayan, Afshin, Crow, Mary, Van Steenkiste, Christophe, and Verset, Gontran

Published
2023
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49. Sublethal necroptosis signaling promotes inflammation and liver cancer

Author

Vucur, Mihael, Ghallab, Ahmed, Schneider, Anne T., Adili, Arlind, Cheng, Mingbo, Castoldi, Mirco, Singer, Michael T., Büttner, Veronika, Keysberg, Leonie S., Küsgens, Lena, Kohlhepp, Marlene, Görg, Boris, Gallage, Suchira, Barragan Avila, Jose Efren, Unger, Kristian, Kordes, Claus, Leblond, Anne-Laure, Albrecht, Wiebke, Loosen, Sven H., Lohr, Carolin, Jördens, Markus S., Babler, Anne, Hayat, Sikander, Schumacher, David, Koenen, Maria T., Govaere, Olivier, Boekschoten, Mark V., Jörs, Simone, Villacorta-Martin, Carlos, Mazzaferro, Vincenzo, Llovet, Josep M., Weiskirchen, Ralf, Kather, Jakob N., Starlinger, Patrick, Trauner, Michael, Luedde, Mark, Heij, Lara R., Neumann, Ulf P., Keitel, Verena, Bode, Johannes G., Schneider, Rebekka K., Tacke, Frank, Levkau, Bodo, Lammers, Twan, Fluegen, Georg, Alexandrov, Theodore, Collins, Amy L., Nelson, Glyn, Oakley, Fiona, Mann, Derek A., Roderburg, Christoph, Longerich, Thomas, Weber, Achim, Villanueva, Augusto, Samson, Andre L., Murphy, James M., Kramann, Rafael, Geisler, Fabian, Costa, Ivan G., Hengstler, Jan G., Heikenwalder, Mathias, and Luedde, Tom

Published
2023
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