Papers
Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training
Charbel Sakr, Steve Dai, Rangha Venkatesan et al.
Optimal Clustering with Noisy Queries via Multi-Armed Bandit
Jinghui Xia, Zengfeng Huang
Optimal Estimation of Policy Gradient via Double Fitted Iteration
Chengzhuo Ni, Ruiqi Zhang, Xiang Ji et al.
Optimally Controllable Perceptual Lossy Compression
Zeyu Yan, Fei Wen, Peilin Liu
Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer
Lucas Nunes Alegre, Ana Bazzan, Bruno C. Da Silva
Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training
Risheng Liu, Xuan Liu, Shangzhi Zeng et al.
Optimization-Induced Graph Implicit Nonlinear Diffusion
Qi Chen, Yifei Wang, Yisen Wang et al.
Optimizing Sequential Experimental Design with Deep Reinforcement Learning
Tom Blau, Edwin V. Bonilla, Iadine Chades et al.
Optimizing Tensor Network Contraction Using Reinforcement Learning
Eli Meirom, Haggai Maron, Shie Mannor et al.
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering
Ekdeep Lubana, Chi Ian Tang, Fahim Kawsar et al.
Order Constraints in Optimal Transport
Yu Chin Fabian Lim, Laura Wynter, Shiau Hong Lim
Out-of-Distribution Detection with Deep Nearest Neighbors
Yiyou Sun, Yifei Ming, Xiaojin Zhu et al.
Overcoming Oscillations in Quantization-Aware Training
Markus Nagel, Marios Fournarakis, Yelysei Bondarenko et al.
PAC-Bayesian Bounds on Rate-Efficient Classifiers
Alhabib Abbas, Yiannis Andreopoulos
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs
Zehao Dong, Muhan Zhang, Fuhai Li et al.
PAC-Net: A Model Pruning Approach to Inductive Transfer Learning
Sanghoon Myung, In Huh, Wonik Jang et al.
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation
Matilde Gargiani, Andrea Zanelli, Andrea Martinelli et al.
Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding
Kazuma K Tsuji, Ken’Ichiro Tanaka, Sebastian Pokutta
Parametric Visual Program Induction with Function Modularization
Xuguang Duan, Xin Wang, Ziwei Zhang et al.
Parsimonious Learning-Augmented Caching
Sungjin Im, Ravi Kumar, Aditya Petety et al.
Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition
Haotao Wang, Aston Zhang, Yi Zhu et al.
Partial Counterfactual Identification from Observational and Experimental Data
Junzhe Zhang, Jin Tian, Elias Bareinboim
Partial disentanglement for domain adaptation
Lingjing Kong, Shaoan Xie, Weiran Yao et al.
Partial Label Learning via Label Influence Function
Xiuwen Gong, Dong Yuan, Wei Bao
Particle Transformer for Jet Tagging
Huilin Qu, Congqiao Li, Sitian Qian