192 results on '"Caiwen Ding"'
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52. HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU.
53. Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML.
54. FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator.
55. A Compression-Compilation Framework for On-mobile Real-time BERT Applications.
56. Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation.
57. Against Membership Inference Attack: Pruning is All You Need.
58. TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators.
59. Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning.
60. An End-to-end Multi-task Object Detection using Embedded GPU in Autonomous Driving.
61. Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices.
62. A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods.
63. Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning.
64. FTRANS: energy-efficient acceleration of transformers using FPGA.
65. A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework.
66. Towards an Efficient and General Framework of Robust Training for Graph Neural Networks.
67. Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation.
68. An Efficient Deep Reinforcement Learning Framework for UAVs.
69. A DNN Compression Framework for SOT-MRAM-based Processing-In-Memory Engine.
70. FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability.
71. QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity.
72. An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM.
73. A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.
74. A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology.
75. E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs.
76. REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs.
77. Deep Compressed Pneumonia Detection for Low-Power Embedded Devices.
78. VIBNN: Hardware Acceleration of Bayesian Neural Networks.
79. Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs.
80. Learning Topics Using Semantic Locality.
81. C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs.
82. Prediction-based fast thermoelectric generator reconfiguration for energy harvesting from vehicle radiators.
83. FFT-based deep learning deployment in embedded systems.
84. Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks Using Stochastic Computing.
85. A Fast and Effective Memristor-Based Method for Finding Approximate Eigenvalues and Eigenvectors of Non-negative Matrices.
86. Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework.
87. Memristor-Based Spectral Decomposition of Matrices and Its Applications
88. SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing.
89. CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices.
90. Reconfigurable thermoelectric generators for vehicle radiators energy harvesting.
91. Softmax Regression Design for Stochastic Computing Based Deep Convolutional Neural Networks.
92. Memristor crossbar-based ultra-efficient next-generation baseband processors.
93. Algorithm accelerations for luminescent solar concentrator-enhanced reconfigurable onboard photovoltaic system.
94. Towards acceleration of deep convolutional neural networks using stochastic computing.
95. Hardware-driven nonlinear activation for stochastic computing based deep convolutional neural networks.
96. Dr. Top-k: delegate-centric Top-k on GPUs.
97. E.T.: re-thinking self-attention for transformer models on GPUs.
98. Neural Network-based Prediction Algorithms for In-Door Multi-Source Energy Harvesting System for Non-Volatile Processors.
99. Multi-source in-door energy harvesting for non-volatile processors.
100. Luminescent solar concentrator-based photovoltaic reconfiguration for hybrid and plug-in electric vehicles.
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