Papers
11,015 papers found
Optimization inspired Multi-Branch Equilibrium Models
Mingjie Li, Yisen Wang, Xingyu Xie et al.
Optimizer Amalgamation
Tianshu Huang, Tianlong Chen, Sijia Liu et al.
Optimizing Neural Networks with Gradient Lexicase Selection
Li Ding, Lee Spector
Orchestrated Value Mapping for Reinforcement Learning
Mehdi Fatemi, Arash Tavakoli
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations
Aahlad Manas Puli, Lily H Zhang, Eric Karl Oermann et al.
Overcoming The Spectral Bias of Neural Value Approximation
Ge Yang, Anurag Ajay, Pulkit Agrawal
PAC-Bayes Information Bottleneck
Zifeng Wang, Shao-Lun Huang, Ercan Engin Kuruoglu et al.
PAC Prediction Sets Under Covariate Shift
Sangdon Park, Edgar Dobriban, Insup Lee et al.
P-Adapters: Robustly Extracting Factual Information from Language Models with Diverse Prompts
Benjamin Newman, Prafulla Kumar Choubey, Nazneen Rajani
Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences
Euhyun Moon, Eric C Cyr
Pareto Policy Adaptation
Panagiotis Kyriakis, Jyotirmoy Deshmukh, Paul Bogdan
Pareto Policy Pool for Model-based Offline Reinforcement Learning
Yijun Yang, Jing Jiang, Tianyi Zhou et al.
Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization
Xi Lin, Zhiyuan Yang, Qingfu Zhang
Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration
Ziming Wang, Nan Xue, Ling Lei et al.
Particle Stochastic Dual Coordinate Ascent: Exponential convergent algorithm for mean field neural network optimization
Kazusato Oko, Taiji Suzuki, Atsushi Nitanda et al.
Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?
Yonggan Fu, Shunyao Zhang, Shang Wu et al.
Path Auxiliary Proposal for MCMC in Discrete Space
Haoran Sun, Hanjun Dai, Wei Xia et al.
Path Integral Sampler: A Stochastic Control Approach For Sampling
Qinsheng Zhang, Yongxin Chen
PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning
Seng Pei Liew, Tsubasa Takahashi, Michihiko Ueno
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently
Xiaohan Chen, Jason Zhang, Zhangyang Wang
Perceiver IO: A General Architecture for Structured Inputs & Outputs
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac et al.
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method
Ziwei Guan, Tengyu Xu, Yingbin Liang
Permutation-Based SGD: Is Random Optimal?
Shashank Rajput, Kangwook Lee, Dimitris Papailiopoulos
Permutation Compressors for Provably Faster Distributed Nonconvex Optimization
Rafał Szlendak, Alexander Tyurin, Peter Richtárik
Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning
Chenjia Bai, Lingxiao Wang, Zhuoran Yang et al.