Papers
11,951 papers found
Benchmarks for Deep Off-Policy Evaluation
Justin Fu, Mohammad Norouzi, Ofir Nachum et al.
BERTology Meets Biology: Interpreting Attention in Protein Language Models
Jesse Vig, Ali Madani, Lav R. Varshney et al.
Better Fine-Tuning by Reducing Representational Collapse
Armen Aghajanyan, Akshat Shrivastava, Anchit Gupta et al.
Beyond Categorical Label Representations for Image Classification
Boyuan Chen, Yu Li, Sunand Raghupathi et al.
Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters
Aston Zhang, Yi Tay, SHUAI Zhang et al.
Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech
Yoonhyung Lee, Joongbo Shin, Kyomin Jung
BiPointNet: Binary Neural Network for Point Clouds
Haotong Qin, Zhongang Cai, Mingyuan Zhang et al.
Black-Box Reductions for Zeroth-Order Gradient Algorithms to Achieve Lower Query Complexity
Bin Gu, Xiyuan Wei, Shangqian Gao et al.
Blending MPC & Value Function Approximation for Efficient Reinforcement Learning
Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots
BOIL: Towards Representation Change for Few-shot Learning
Jaehoon Oh, Hyungjun Yoo, ChangHwan Kim et al.
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Sergei Ivanov, Liudmila Prokhorenkova
Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis
Zhipeng Bao, Yu-Xiong Wang, Martial Hebert
BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
Yuhang Li, Ruihao Gong, Xu Tan et al.
BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization
Huanrui Yang, Lin Duan, Yiran Chen et al.
BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration
Augustus Odena, Kensen Shi, David Bieber et al.
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification
Yingxue Zhou, Steven Wu, Arindam Banerjee
Byzantine-Resilient Non-Convex Stochastic Gradient Descent
Zeyuan Allen-Zhu, Faeze Ebrahimianghazani, Jerry Li et al.
Calibration of Neural Networks using Splines
Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan et al.
Calibration tests beyond classification
David Widmann, Fredrik Lindsten, Dave Zachariah
Can a Fruit Fly Learn Word Embeddings?
Yuchen Liang, Chaitanya Ryali, Benjamin Hoover et al.
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta et al.
CaPC Learning: Confidential and Private Collaborative Learning
Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic et al.
Capturing Label Characteristics in VAEs
Tom Joy, Sebastian Schmon, Philip Torr et al.
Categorical Normalizing Flows via Continuous Transformations
Phillip Lippe, Efstratios Gavves