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1. Modeling Uncertainty in Personalized Emotion Prediction with Normalizing Flows

Author

Miłkowski, Piotr, Karanowski, Konrad, Wielopolski, Patryk, Kocoń, Jan, Kazienko, Przemysław, and Zięba, Maciej

Subjects
Computer Science - Artificial Intelligence
Abstract

Designing predictive models for subjective problems in natural language processing (NLP) remains challenging. This is mainly due to its non-deterministic nature and different perceptions of the content by different humans. It may be solved by Personalized Natural Language Processing (PNLP), where the model exploits additional information about the reader to make more accurate predictions. However, current approaches require complete information about the recipients to be straight embedded. Besides, the recent methods focus on deterministic inference or simple frequency-based estimations of the probabilities. In this work, we overcome this limitation by proposing a novel approach to capture the uncertainty of the forecast using conditional Normalizing Flows. This allows us to model complex multimodal distributions and to compare various models using negative log-likelihood (NLL). In addition, the new solution allows for various interpretations of possible reader perception thanks to the available sampling function. We validated our method on three challenging, subjective NLP tasks, including emotion recognition and hate speech. The comparative analysis of generalized and personalized approaches revealed that our personalized solutions significantly outperform the baseline and provide more precise uncertainty estimates. The impact on the text interpretability and uncertainty studies are presented as well. The information brought by the developed methods makes it possible to build hybrid models whose effectiveness surpasses classic solutions. In addition, an analysis and visualization of the probabilities of the given decisions for texts with high entropy of annotations and annotators with mixed views were carried out., Comment: 10 pages, 8 figures, SENTIRE'23 (ICDM 2023)

Published
2023

3. LA DOLCE VITA: Less than a year after an onstage heart attack took him out of action, A1 Di Meola is back on the road and releasing his most ambitious work to date, the double-album Twentyfour. Says the unstoppable virtuoso, 'This is a new beginning for me.'

Author

Milkowski, Bill

Subjects
Guitarists, Consumer news and advice, General interest, Music
Abstract

THE ONSTAGE BACKDROP for Al Di Meola's Electric Years Tour is a huge collage of 17 of his most recognizable album covers. Noticeably absent from the bunch is his groundbreaking [...]

Published
2024

4. 'YOUR INFLUENCES STICK WITH YOU: Scott Henderson spent lockdown training his ears and building improv skills. As Karnevel! shows, his jazz chops flourished, but his blues-rock roots remain as strong as ever

Author

Milkowski, Bill

Subjects
Rock musicians -- Training, Guitarists -- Training, Consumer news and advice, General interest, Music
Abstract

GROWING UPAS a die-hard blues-rocker in 1970s South Florida, Scott Henderson fell in love with the sounds of that era's big-name rock guitarists. 'Ritchie Blackmore, Jimmy Page, Jeff Beck... I [...]

Published
2024

5. ChatGPT: Jack of all trades, master of none

Author

Kocoń, Jan, Cichecki, Igor, Kaszyca, Oliwier, Kochanek, Mateusz, Szydło, Dominika, Baran, Joanna, Bielaniewicz, Julita, Gruza, Marcin, Janz, Arkadiusz, Kanclerz, Kamil, Kocoń, Anna, Koptyra, Bartłomiej, Mieleszczenko-Kowszewicz, Wiktoria, Miłkowski, Piotr, Oleksy, Marcin, Piasecki, Maciej, Radliński, Łukasz, Wojtasik, Konrad, Woźniak, Stanisław, and Kazienko, Przemysław

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computers and Society, Computer Science - Machine Learning
Abstract

OpenAI has released the Chat Generative Pre-trained Transformer (ChatGPT) and revolutionized the approach in artificial intelligence to human-model interaction. Several publications on ChatGPT evaluation test its effectiveness on well-known natural language processing (NLP) tasks. However, the existing studies are mostly non-automated and tested on a very limited scale. In this work, we examined ChatGPT's capabilities on 25 diverse analytical NLP tasks, most of them subjective even to humans, such as sentiment analysis, emotion recognition, offensiveness, and stance detection. In contrast, the other tasks require more objective reasoning like word sense disambiguation, linguistic acceptability, and question answering. We also evaluated GPT-4 model on five selected subsets of NLP tasks. We automated ChatGPT and GPT-4 prompting process and analyzed more than 49k responses. Our comparison of its results with available State-of-the-Art (SOTA) solutions showed that the average loss in quality of the ChatGPT model was about 25% for zero-shot and few-shot evaluation. For GPT-4 model, a loss for semantic tasks is significantly lower than for ChatGPT. We showed that the more difficult the task (lower SOTA performance), the higher the ChatGPT loss. It especially refers to pragmatic NLP problems like emotion recognition. We also tested the ability to personalize ChatGPT responses for selected subjective tasks via Random Contextual Few-Shot Personalization, and we obtained significantly better user-based predictions. Additional qualitative analysis revealed a ChatGPT bias, most likely due to the rules imposed on human trainers by OpenAI. Our results provide the basis for a fundamental discussion of whether the high quality of recent predictive NLP models can indicate a tool's usefulness to society and how the learning and validation procedures for such systems should be established., Comment: preprint

Published
2023
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8. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Author

Srivastava, Aarohi, Rastogi, Abhinav, Rao, Abhishek, Shoeb, Abu Awal Md, Abid, Abubakar, Fisch, Adam, Brown, Adam R., Santoro, Adam, Gupta, Aditya, Garriga-Alonso, Adrià, Kluska, Agnieszka, Lewkowycz, Aitor, Agarwal, Akshat, Power, Alethea, Ray, Alex, Warstadt, Alex, Kocurek, Alexander W., Safaya, Ali, Tazarv, Ali, Xiang, Alice, Parrish, Alicia, Nie, Allen, Hussain, Aman, Askell, Amanda, Dsouza, Amanda, Slone, Ambrose, Rahane, Ameet, Iyer, Anantharaman S., Andreassen, Anders, Madotto, Andrea, Santilli, Andrea, Stuhlmüller, Andreas, Dai, Andrew, La, Andrew, Lampinen, Andrew, Zou, Andy, Jiang, Angela, Chen, Angelica, Vuong, Anh, Gupta, Animesh, Gottardi, Anna, Norelli, Antonio, Venkatesh, Anu, Gholamidavoodi, Arash, Tabassum, Arfa, Menezes, Arul, Kirubarajan, Arun, Mullokandov, Asher, Sabharwal, Ashish, Herrick, Austin, Efrat, Avia, Erdem, Aykut, Karakaş, Ayla, Roberts, B. Ryan, Loe, Bao Sheng, Zoph, Barret, Bojanowski, Bartłomiej, Özyurt, Batuhan, Hedayatnia, Behnam, Neyshabur, Behnam, Inden, Benjamin, Stein, Benno, Ekmekci, Berk, Lin, Bill Yuchen, Howald, Blake, Orinion, Bryan, Diao, Cameron, Dour, Cameron, Stinson, Catherine, Argueta, Cedrick, Ramírez, César Ferri, Singh, Chandan, Rathkopf, Charles, Meng, Chenlin, Baral, Chitta, Wu, Chiyu, Callison-Burch, Chris, Waites, Chris, Voigt, Christian, Manning, Christopher D., Potts, Christopher, Ramirez, Cindy, Rivera, Clara E., Siro, Clemencia, Raffel, Colin, Ashcraft, Courtney, Garbacea, Cristina, Sileo, Damien, Garrette, Dan, Hendrycks, Dan, Kilman, Dan, Roth, Dan, Freeman, Daniel, Khashabi, Daniel, Levy, Daniel, González, Daniel Moseguí, Perszyk, Danielle, Hernandez, Danny, Chen, Danqi, Ippolito, Daphne, Gilboa, Dar, Dohan, David, Drakard, David, Jurgens, David, Datta, Debajyoti, Ganguli, Deep, Emelin, Denis, Kleyko, Denis, Yuret, Deniz, Chen, Derek, Tam, Derek, Hupkes, Dieuwke, Misra, Diganta, Buzan, Dilyar, Mollo, Dimitri Coelho, Yang, Diyi, Lee, Dong-Ho, Schrader, Dylan, Shutova, Ekaterina, Cubuk, Ekin Dogus, Segal, Elad, Hagerman, Eleanor, Barnes, Elizabeth, Donoway, Elizabeth, Pavlick, Ellie, Rodola, Emanuele, Lam, Emma, Chu, Eric, Tang, Eric, Erdem, Erkut, Chang, Ernie, Chi, Ethan A., Dyer, Ethan, Jerzak, Ethan, Kim, Ethan, Manyasi, Eunice Engefu, Zheltonozhskii, Evgenii, Xia, Fanyue, Siar, Fatemeh, Martínez-Plumed, Fernando, Happé, Francesca, Chollet, Francois, Rong, Frieda, Mishra, Gaurav, Winata, Genta Indra, de Melo, Gerard, Kruszewski, Germán, Parascandolo, Giambattista, Mariani, Giorgio, Wang, Gloria, Jaimovitch-López, Gonzalo, Betz, Gregor, Gur-Ari, Guy, Galijasevic, Hana, Kim, Hannah, Rashkin, Hannah, Hajishirzi, Hannaneh, Mehta, Harsh, Bogar, Hayden, Shevlin, Henry, Schütze, Hinrich, Yakura, Hiromu, Zhang, Hongming, Wong, Hugh Mee, Ng, Ian, Noble, Isaac, Jumelet, Jaap, Geissinger, Jack, Kernion, Jackson, Hilton, Jacob, Lee, Jaehoon, Fisac, Jaime Fernández, Simon, James B., Koppel, James, Zheng, James, Zou, James, Kocoń, Jan, Thompson, Jana, Wingfield, Janelle, Kaplan, Jared, Radom, Jarema, Sohl-Dickstein, Jascha, Phang, Jason, Wei, Jason, Yosinski, Jason, Novikova, Jekaterina, Bosscher, Jelle, Marsh, Jennifer, Kim, Jeremy, Taal, Jeroen, Engel, Jesse, Alabi, Jesujoba, Xu, Jiacheng, Song, Jiaming, Tang, Jillian, Waweru, Joan, Burden, John, Miller, John, Balis, John U., Batchelder, Jonathan, Berant, Jonathan, Frohberg, Jörg, Rozen, Jos, Hernandez-Orallo, Jose, Boudeman, Joseph, Guerr, Joseph, Jones, Joseph, Tenenbaum, Joshua B., Rule, Joshua S., Chua, Joyce, Kanclerz, Kamil, Livescu, Karen, Krauth, Karl, Gopalakrishnan, Karthik, Ignatyeva, Katerina, Markert, Katja, Dhole, Kaustubh D., Gimpel, Kevin, Omondi, Kevin, Mathewson, Kory, Chiafullo, Kristen, Shkaruta, Ksenia, Shridhar, Kumar, McDonell, Kyle, Richardson, Kyle, Reynolds, Laria, Gao, Leo, Zhang, Li, Dugan, Liam, Qin, Lianhui, Contreras-Ochando, Lidia, Morency, Louis-Philippe, Moschella, Luca, Lam, Lucas, Noble, Lucy, Schmidt, Ludwig, He, Luheng, Colón, Luis Oliveros, Metz, Luke, Şenel, Lütfi Kerem, Bosma, Maarten, Sap, Maarten, ter Hoeve, Maartje, Farooqi, Maheen, Faruqui, Manaal, Mazeika, Mantas, Baturan, Marco, Marelli, Marco, Maru, Marco, Quintana, Maria Jose Ramírez, Tolkiehn, Marie, Giulianelli, Mario, Lewis, Martha, Potthast, Martin, Leavitt, Matthew L., Hagen, Matthias, Schubert, Mátyás, Baitemirova, Medina Orduna, Arnaud, Melody, McElrath, Melvin, Yee, Michael A., Cohen, Michael, Gu, Michael, Ivanitskiy, Michael, Starritt, Michael, Strube, Michael, Swędrowski, Michał, Bevilacqua, Michele, Yasunaga, Michihiro, Kale, Mihir, Cain, Mike, Xu, Mimee, Suzgun, Mirac, Walker, Mitch, Tiwari, Mo, Bansal, Mohit, Aminnaseri, Moin, Geva, Mor, Gheini, Mozhdeh, T, Mukund Varma, Peng, Nanyun, Chi, Nathan A., Lee, Nayeon, Krakover, Neta Gur-Ari, Cameron, Nicholas, Roberts, Nicholas, Doiron, Nick, Martinez, Nicole, Nangia, Nikita, Deckers, Niklas, Muennighoff, Niklas, Keskar, Nitish Shirish, Iyer, Niveditha S., Constant, Noah, Fiedel, Noah, Wen, Nuan, Zhang, Oliver, Agha, Omar, Elbaghdadi, Omar, Levy, Omer, Evans, Owain, Casares, Pablo Antonio Moreno, Doshi, Parth, Fung, Pascale, Liang, Paul Pu, Vicol, Paul, Alipoormolabashi, Pegah, Liao, Peiyuan, Liang, Percy, Chang, Peter, Eckersley, Peter, Htut, Phu Mon, Hwang, Pinyu, Miłkowski, Piotr, Patil, Piyush, Pezeshkpour, Pouya, Oli, Priti, Mei, Qiaozhu, Lyu, Qing, Chen, Qinlang, Banjade, Rabin, Rudolph, Rachel Etta, Gabriel, Raefer, Habacker, Rahel, Risco, Ramon, Millière, Raphaël, Garg, Rhythm, Barnes, Richard, Saurous, Rif A., Arakawa, Riku, Raymaekers, Robbe, Frank, Robert, Sikand, Rohan, Novak, Roman, Sitelew, Roman, LeBras, Ronan, Liu, Rosanne, Jacobs, Rowan, Zhang, Rui, Salakhutdinov, Ruslan, Chi, Ryan, Lee, Ryan, Stovall, Ryan, Teehan, Ryan, Yang, Rylan, Singh, Sahib, Mohammad, Saif M., Anand, Sajant, Dillavou, Sam, Shleifer, Sam, Wiseman, Sam, Gruetter, Samuel, Bowman, Samuel R., Schoenholz, Samuel S., Han, Sanghyun, Kwatra, Sanjeev, Rous, Sarah A., Ghazarian, Sarik, Ghosh, Sayan, Casey, Sean, Bischoff, Sebastian, Gehrmann, Sebastian, Schuster, Sebastian, Sadeghi, Sepideh, Hamdan, Shadi, Zhou, Sharon, Srivastava, Shashank, Shi, Sherry, Singh, Shikhar, Asaadi, Shima, Gu, Shixiang Shane, Pachchigar, Shubh, Toshniwal, Shubham, Upadhyay, Shyam, Shyamolima, Debnath, Shakeri, Siamak, Thormeyer, Simon, Melzi, Simone, Reddy, Siva, Makini, Sneha Priscilla, Lee, Soo-Hwan, Torene, Spencer, Hatwar, Sriharsha, Dehaene, Stanislas, Divic, Stefan, Ermon, Stefano, Biderman, Stella, Lin, Stephanie, Prasad, Stephen, Piantadosi, Steven T., Shieber, Stuart M., Misherghi, Summer, Kiritchenko, Svetlana, Mishra, Swaroop, Linzen, Tal, Schuster, Tal, Li, Tao, Yu, Tao, Ali, Tariq, Hashimoto, Tatsu, Wu, Te-Lin, Desbordes, Théo, Rothschild, Theodore, Phan, Thomas, Wang, Tianle, Nkinyili, Tiberius, Schick, Timo, Kornev, Timofei, Tunduny, Titus, Gerstenberg, Tobias, Chang, Trenton, Neeraj, Trishala, Khot, Tushar, Shultz, Tyler, Shaham, Uri, Misra, Vedant, Demberg, Vera, Nyamai, Victoria, Raunak, Vikas, Ramasesh, Vinay, Prabhu, Vinay Uday, Padmakumar, Vishakh, Srikumar, Vivek, Fedus, William, Saunders, William, Zhang, William, Vossen, Wout, Ren, Xiang, Tong, Xiaoyu, Zhao, Xinran, Wu, Xinyi, Shen, Xudong, Yaghoobzadeh, Yadollah, Lakretz, Yair, Song, Yangqiu, Bahri, Yasaman, Choi, Yejin, Yang, Yichi, Hao, Yiding, Chen, Yifu, Belinkov, Yonatan, Hou, Yu, Hou, Yufang, Bai, Yuntao, Seid, Zachary, Zhao, Zhuoye, Wang, Zijian, Wang, Zijie J., Wang, Zirui, and Wu, Ziyi

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computers and Society, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabilities are as yet poorly characterized. In order to inform future research, prepare for disruptive new model capabilities, and ameliorate socially harmful effects, it is vital that we understand the present and near-future capabilities and limitations of language models. To address this challenge, we introduce the Beyond the Imitation Game benchmark (BIG-bench). BIG-bench currently consists of 204 tasks, contributed by 450 authors across 132 institutions. Task topics are diverse, drawing problems from linguistics, childhood development, math, common-sense reasoning, biology, physics, social bias, software development, and beyond. BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models. We evaluate the behavior of OpenAI's GPT models, Google-internal dense transformer architectures, and Switch-style sparse transformers on BIG-bench, across model sizes spanning millions to hundreds of billions of parameters. In addition, a team of human expert raters performed all tasks in order to provide a strong baseline. Findings include: model performance and calibration both improve with scale, but are poor in absolute terms (and when compared with rater performance); performance is remarkably similar across model classes, though with benefits from sparsity; tasks that improve gradually and predictably commonly involve a large knowledge or memorization component, whereas tasks that exhibit "breakthrough" behavior at a critical scale often involve multiple steps or components, or brittle metrics; social bias typically increases with scale in settings with ambiguous context, but this can be improved with prompting., Comment: 27 pages, 17 figures + references and appendices, repo: https://github.com/google/BIG-bench

Published
2022

9. THE art of BEING OZ: His gigs are laboratories for sonic experimentation. As he drops his new powerhouse album Triple Play, Oz Noy tells us how looping and pedal precision became central to his process

Author

Milkowski, Bill

Subjects
Guitarists, Dancing -- Dance reviews, Consumer news and advice, General interest, Music
Abstract

WHILE SOME GUITARISTS are adept at tweaking their tones through a variety of effects from song to song, Israel-born fusion maverick Oz Noy is like a virtuoso tap dancer on [...]

Published
2024

10. ONE FROM THE HEART: Grieving the loss of his grandparents and friend Joey DeFrancesco, jazz guitar ace Dan Wilson found solace in music. On Things Eternal, he dazzles on both a diverse array of covers and on originals that 'memorialize the folks that I lost'

Author

Milkowski, Bill

Subjects
Guitarists -- Appreciation, Consumer news and advice, General interest, Music
Abstract

THERE WAS NO denying Dan Wilson's talents, nor the diversity of his repertoire, when he released Vessel of Wood and Earth in 2021. They shone through on every track. The [...]

Published
2023

13. MATTEO MANCUSO IS LIGHT YEARS AHEAD OF US ALL: When it comes to improvisation, Italy's fingerstyle fusion maestro leaves the best players in the dust. Says Al Di Meola, 'It would take two, three lifetimes to catch up with him.'

Author

Milkowski, Bill

Subjects
Internet videos, Consumer news and advice, General interest, Music
Abstract

It was just before the pandemic hit in 2020 that I happened upon a YouTube video by an Italian funk-fusion trio named the Snips. The initial hook for me was [...]

Published
2023

18. Language Report Polish

Author

Ogrodniczuk, Maciej, Pęzik, Piotr, Łaziński, Marek, Miłkowski, Marcin, Sonntag, Daniel, Editor-in-Chief, Rehm, Georg, editor, and Way, Andy, editor

Published
2023
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20. Still Killing: Fifty-five years since his solo bow, Harvey Mandel shows no sign of slowing down on his latest, Who's Calling. 'The Sustain King' riffs with GP on his music, guitar technique and a certain player by the name of Eddie

Author

Milkowski, Bill

Subjects
Who's Calling (Sound recording), Guitarists -- Interviews, Consumer news and advice, General interest, Music
Abstract

TWO LANDMARK GUITAR releases, both solo debuts, came along within a few months of each other in 1968 to open my youthful ears and blow my 14-year-old mind. And yet, [...]

Published
2023

22. Mechanistic Development of Cancers Associated with Processed Meat Products: A Review

Author

Andrew Milkowski, Charles J. Czuprynski, Mark Richards, and Wendy Bedale

Subjects
mechanisms of carcinogenesis, mutagenesis, cancer, processed meat, Animal culture, SF1-1100, Nutrition. Foods and food supply, TX341-641
Abstract

Epidemiological data link processed meat products to various cancers, especially colorectal cancer; however,such evidence cannot prove causation. Clear mechanistic evidence of how these foods promote carcinogenesis strengthens the case for causation. Because the complexity and heterogeneity of processed meats as a food category complicate both epidemiological and mechanistic assessments, the study of carcinogenic mechanisms associated with specific components of such foods is often undertaken. These include components that are intrinsic to meats, those that contaminate meat, and those ingredients that are added to or form in meats during processing. Consumption of processed meats also leads to endogenous production of agents, epigenetic changes, and alterations in the microbiota of the digestive tract; therefore,the potential contributions of these endogenous responses to carcinogenesis are also discussed. This review highlights data that illuminate potential mechanisms by which agents associated with processed meats (including processed poultry) could contribute to carcinogenesis. The potential for personal factors such as overall diet, cooking methods, genetic variation, and inflammation and infection status to influence these carcinogenic mechanisms is also summarized. Because the intended audience of this review includes those who may be less familiar with current general mechanisms of mutagenesis and carcinogenesis, detailed background on these topics is provided.

Published
2023
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25. Lack or insufficient predialysis nephrology care worsens the outcomes in dialyzed patients – call for action

Author

Andrzej Milkowski, Tomasz Prystacki, Wojciech Marcinkowski, Teresa Dryl-Rydzynska, Jacek Zawierucha, Jacek S. Malyszko, Pawel Zebrowski, Konrad Zuzda, and Jolanta Małyszko

Subjects
Late referral, vascular access, hemodialysis, outcome, predialysis care, Diseases of the genitourinary system. Urology, RC870-923
Abstract

The phenomenon of patients with advanced renal failure accepted for dialysis at a late stage in the disease process (late referral [LR]) is known almost from the beginning of dialysis therapy. It may also be associated with worse outcomes. The aim of the study was to assess the effect of referral time on the outcomes, such as number of hospitalizations, length of stay, kidney transplantation, and mortality. A study of 1303 patients with end-stage renal failure admitted for dialysis in the same period in Fresenius Nephrocare Poland dialysis centers was initiated. The type of vascular access during the first dialysis was accepted as the criterion differentiating LR (n = 457 with acute catheter) from early referral (ER; n = 846). The primary endpoint was the occurrence of death during the 13-month observation. By the end of observation, 341 (26.2%) of patients died. The frequency of death was 18.1 for ER and 37.9 for LR per 1000 patient-months. It can be estimated that 52.1% (95% CI: 40.5–61.5%) of the 341 deaths were caused by belonging to the LR group. Patients from LR group had longer hospitalizations, more malignancies, lower rate of vascular access in the form of a–v fistula, higher comorbidity index. It seems that establishing a nephrological registry would help to improve the organization of care for patients with kidney disease, particularly in the pandemic era.

Published
2022
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36. Multi-Wiki90k: Multilingual Benchmark Dataset for Paragraph Segmentation

Author

Swędrowski, Michał, Miłkowski, Piotr, Bojanowski, Bartłomiej, Kocoń, Jan, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Bădică, Costin, editor, Treur, Jan, editor, Benslimane, Djamal, editor, Hnatkowska, Bogumiła, editor, and Krótkiewicz, Marek, editor

Published
2022
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37. Multi-module Natural Language Search Engine for Travel Offers

Author

Gawron, Karol, Wojtasik, Konrad, Bojanowski, Bartłomiej, Janz, Arkadiusz, Kocoń, Jan, Krupa, Tomasz, Kukałowicz, Agnieszka, Miłkowski, Piotr, Piasecki, Maciej, Pogoda, Michał, Ropiak, Norbert, Swędrowski, Michał, Walentynowicz, Wiktor, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Bădică, Costin, editor, Treur, Jan, editor, Benslimane, Djamal, editor, Hnatkowska, Bogumiła, editor, and Krótkiewicz, Marek, editor

Published
2022
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38. Multi-model Analysis of Language-Agnostic Sentiment Classification on MultiEmo Data

Author

Miłkowski, Piotr, Gruza, Marcin, Kazienko, Przemysław, Szołomicka, Joanna, Woźniak, Stanisław, Kocoń, Jan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nguyen, Ngoc Thanh, editor, Manolopoulos, Yannis, editor, Chbeir, Richard, editor, Kozierkiewicz, Adrianna, editor, and Trawiński, Bogdan, editor

Published
2022
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39. Neuro-Symbolic Models for Sentiment Analysis

Author

Kocoń, Jan, Baran, Joanna, Gruza, Marcin, Janz, Arkadiusz, Kajstura, Michał, Kazienko, Przemysław, Korczyński, Wojciech, Miłkowski, Piotr, Piasecki, Maciej, Szołomicka, Joanna, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Groen, Derek, editor, de Mulatier, Clélia, editor, Paszynski, Maciej, editor, Krzhizhanovskaya, Valeria V., editor, Dongarra, Jack J., editor, and Sloot, Peter M. A., editor

Published
2022
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40. MultiEmo: Language-Agnostic Sentiment Analysis

Author

Miłkowski, Piotr, Gruza, Marcin, Kazienko, Przemysław, Szołomicka, Joanna, Woźniak, Stanisław, Kocoń, Jan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Groen, Derek, editor, de Mulatier, Clélia, editor, Paszynski, Maciej, editor, Krzhizhanovskaya, Valeria V., editor, Dongarra, Jack J., editor, and Sloot, Peter M. A., editor

Published
2022
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41. Multilingual and Language-Agnostic Recognition of Emotions, Valence and Arousal in Large-Scale Multi-domain Text Reviews

Author

Kocoń, Jan, Miłkowski, Piotr, Wierzba, Małgorzata, Konat, Barbara, Klessa, Katarzyna, Janz, Arkadiusz, Riegel, Monika, Juszczyk, Konrad, Grimling, Damian, Marchewka, Artur, Piasecki, Maciej, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Vetulani, Zygmunt, editor, Paroubek, Patrick, editor, and Kubis, Marek, editor

Published
2022
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42. THE CURIOUS GUITAR OF Bill Jrisell: He treats every note as a question. It's an approach that's made him a favorite of artists across the spectrum. GP asks the guitar legend a few questions of our own

Author

Milkowski, Bill

Subjects
Television broadcasting, Consumer news and advice, General interest, Music
Abstract

When the Beatles made their American debut on The Ed Sullivan Show on February 9, 1964, it inspired a generation of Boomers to pick up the guitar. But it was [...]

Published
2023

43. A GLIMPSE OF A FEELING: With his guitar, looper and effects, Danish guitarist Jakob Bro captures moods in dreamy improvisations. His three recent and new releases are remarkable reflections on the mystery of music

Author

Milkowski, Bill

Subjects
Guitar, Guitarists, Consumer news and advice, General interest, Music
Abstract

THROUGH THE COURSE of five evocative ECM albums, Danish guitarist Jakob Bro has forged a distinctive musical identity with a deft fingerstyle approach to his instrument, along with a penchant [...]

Published
2023

44. The Effect of Commonly Used Organic Acids on the Microbiota of Cured Deli-Style Turkey Breast

Author

Andrew Milkowski, Andrew Steinberger, Garret Suen, Jeff Sindelar, and Mehmet Dogan

Subjects
microbiota, spoilage lactic acid bacteria, antimicrobial organic acids, turkey meat, shelf-life, bacterial community, Animal culture, SF1-1100, Nutrition. Foods and food supply, TX341-641
Abstract

The purpose of this study was to investigate changes in the microbial community structure consisting of spoilage lactic acid bacteria (LAB) when sodium lactate (SL) and SL + sodium diacetate (SD) are included in RTE meat product formulations at concentrations commonly used for controlling Listeria monocytogenes. Sliced cooked, vacuum-packaged turkey breast samples containing no SD or SL (control [C]), 0.125% SD, and the combination of 2.5% SL + 0.125%SD (SLSD) were inoculated with a target of 3 log colony-forming units (CFU)/g of 5 different LAB species (Lactobacillus sakei, Leuconostoc mesenteroides [bacon and deli-shaved ham isolates], Lactococcus lactis, and Enterococcus faecium) and stored at 4°C for 35 d. Microbial community changes were analyzed utilizing 16S ribosomal RNA (rRNA) gene sequencing for the V4 region from the samples collected at days 0, 7, 14, 21, and 35. No significant difference (P>0.05) was observed between the richness of microbial community for all treatments. According to Bray-Curtis dissimilarity matrix and permutational analysis of variance, a significant difference in β-diversity was observed only between C and SLSD (P0.05) was observed for the SD treatment compared with C in the microbiota. According to the results from this study, only SLSD affected the microbial community structure at the beginning of the storage. This study demonstrated that the incorporation of SL in the formulation slowed down the microbial spoilage and the changes in the microbiota of RTE meat products.

Published
2023
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46. Less is More: Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Images

Author

Xu, Zhoubing, Huo, Yuankai, Park, JinHyeong, Landman, Bennett, Milkowski, Andy, Grbic, Sasa, and Zhou, Shaohua

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

An abdominal ultrasound examination, which is the most common ultrasound examination, requires substantial manual efforts to acquire standard abdominal organ views, annotate the views in texts, and record clinically relevant organ measurements. Hence, automatic view classification and landmark detection of the organs can be instrumental to streamline the examination workflow. However, this is a challenging problem given not only the inherent difficulties from the ultrasound modality, e.g., low contrast and large variations, but also the heterogeneity across tasks, i.e., one classification task for all views, and then one landmark detection task for each relevant view. While convolutional neural networks (CNN) have demonstrated more promising outcomes on ultrasound image analytics than traditional machine learning approaches, it becomes impractical to deploy multiple networks (one for each task) due to the limited computational and memory resources on most existing ultrasound scanners. To overcome such limits, we propose a multi-task learning framework to handle all the tasks by a single network. This network is integrated to perform view classification and landmark detection simultaneously; it is also equipped with global convolutional kernels, coordinate constraints, and a conditional adversarial module to leverage the performances. In an experimental study based on 187,219 ultrasound images, with the proposed simplified approach we achieve (1) view classification accuracy better than the agreement between two clinical experts and (2) landmark-based measurement errors on par with inter-user variability. The multi-task approach also benefits from sharing the feature extraction during the training process across all tasks and, as a result, outperforms the approaches that address each task individually., Comment: Accepted to MICCAI 2018

Published
2018

47. THE BUD POWELL OF JAZZ GUITAR: One of the most gifted and musical jazz guitarists of today, Pasquale Grasso takes inspiration not from his six-string brethren but from the genre's legendary ivory ticklers

Author

Milkowski, Bill

Subjects
Concerts, Consumer news and advice, General interest, Music
Abstract

IN 2015, I had the honor of being on a panel of judges for the First Annual Wes Montgomery International Guitar Competition, sponsored by George Klabin of Resonance Records and [...]

Published
2022

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