Papers
11,015 papers found
Posterior sampling for multi-agent reinforcement learning: solving extensive games with imperfect information
Yichi Zhou, Jialian Li, Jun Zhu
Precision Gating: Improving Neural Network Efficiency with Dynamic Dual-Precision Activations
Yichi Zhang, Ritchie Zhao, Weizhe Hua et al.
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control
Nir Levine, Yinlam Chow, Rui Shu et al.
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks
Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz
Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model
Wenhan Xiong, Jingfei Du, William Yang Wang et al.
Pre-training Tasks for Embedding-based Large-scale Retrieval
Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang et al.
Principled Weight Initialization for Hypernetworks
Oscar Chang, Lampros Flokas, Hod Lipson
Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks
Xin Xing, Long Sha, Pengyu Hong et al.
Probability Calibration for Knowledge Graph Embedding Models
Pedro Tabacof, Luca Costabello
Program Guided Agent
Shao-Hua Sun, Te-Lin Wu, Joseph J. Lim
PROGRESSIVE LEARNING AND DISENTANGLEMENT OF HIERARCHICAL REPRESENTATIONS
Zhiyuan Li, Jaideep Vitthal Murkute, Prashnna Kumar Gyawali et al.
Progressive Memory Banks for Incremental Domain Adaptation
Nabiha Asghar, Lili Mou, Kira A. Selby et al.
Projection-Based Constrained Policy Optimization
Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan et al.
Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks
Wei Hu, Lechao Xiao, Jeffrey Pennington
Provable Filter Pruning for Efficient Neural Networks
Lucas Liebenwein, Cenk Baykal, Harry Lang et al.
Provable robustness against all adversarial $l_p$-perturbations for $p\geq 1$
Francesco Croce, Matthias Hein
ProxSGD: Training Structured Neural Networks under Regularization and Constraints
Yang Yang, Yaxiong Yuan, Avraam Chatzimichailidis et al.
Pruned Graph Scattering Transforms
Vassilis N. Ioannidis, Siheng Chen, Georgios B. Giannakis
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
Yurong You, Yan Wang, Wei-Lun Chao et al.
Pure and Spurious Critical Points: a Geometric Study of Linear Networks
Matthew Trager, Kathlén Kohn, Joan Bruna
Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP
Yuanhao Wang, Kefan Dong, Xiaoyu Chen et al.
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel
Xin Qiu, Elliot Meyerson, Risto Miikkulainen
Quantum Algorithms for Deep Convolutional Neural Networks
Iordanis Kerenidis, Jonas Landman, Anupam Prakash
Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box Embeddings
Hongyu Ren*, Weihua Hu*, Jure Leskovec