Papers
8,340 papers found
A Deep Conjugate Direction Method for Iteratively Solving Linear Systems
Ayano Kaneda, Osman Akar, Jingyu Chen et al.
A Distribution Optimization Framework for Confidence Bounds of Risk Measures
Hao Liang, Zhi-Quan Luo
Adversarial Cheap Talk
Chris Lu, Timon Willi, Alistair Letcher et al.
Adversarial Collaborative Learning on Non-IID Features
Qinbin Li, Bingsheng He, Dawn Song
Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples
Chumeng Liang, Xiaoyu Wu, Yang Hua et al.
Adversarial Learning of Distributional Reinforcement Learning
Yang Sui, Yukun Huang, Hongtu Zhu et al.
Adversarially Robust PAC Learnability of Real-Valued Functions
Idan Attias, Steve Hanneke
Adversarial Parameter Attack on Deep Neural Networks
Lijia Yu, Yihan Wang, Xiao-Shan Gao
Adversarial Policies Beat Superhuman Go AIs
Tony Tong Wang, Adam Gleave, Tom Tseng et al.
Adversarial robustness of amortized Bayesian inference
Manuel Gloeckler, Michael Deistler, Jakob H. Macke
A Fast Optimistic Method for Monotone Variational Inequalities
Michael Sedlmayer, Dang-Khoa Nguyen, Radu Ioan Bot
A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel
Mohamad Amin Mohamadi, Wonho Bae, Danica J. Sutherland
A Flexible Diffusion Model
Weitao Du, He Zhang, Tao Yang et al.
A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback
Guanyu Nie, Yididiya Y. Nadew, Yanhui Zhu et al.
A Fully First-Order Method for Stochastic Bilevel Optimization
Jeongyeol Kwon, Dohyun Kwon, Stephen Wright et al.
A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems
Oliver Slumbers, David Henry Mguni, Stefano B Blumberg et al.
A Generalization of ViT/MLP-Mixer to Graphs
Xiaoxin He, Bryan Hooi, Thomas Laurent et al.
A General Representation Learning Framework with Generalization Performance Guarantees
Junbiao Cui, Jianqing Liang, Qin Yue et al.
A Gromov-Wasserstein Geometric View of Spectrum-Preserving Graph Coarsening
Yifan Chen, Rentian Yao, Yun Yang et al.
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining
Shengchao Liu, Weitao Du, Zhi-Ming Ma et al.
A Hybrid Quantum-Classical Approach based on the Hadamard Transform for the Convolutional Layer
Hongyi Pan, Xin Zhu, Salih Furkan Atici et al.
A Kernel-Based View of Language Model Fine-Tuning
Sadhika Malladi, Alexander Wettig, Dingli Yu et al.
A Kernelized Stein Discrepancy for Biological Sequences
Alan Nawzad Amin, Eli N Weinstein, Debora Susan Marks
A Kernel Stein Test of Goodness of Fit for Sequential Models
Jerome Baum, Heishiro Kanagawa, Arthur Gretton
A Large-Scale Study of Probabilistic Calibration in Neural Network Regression
Victor Dheur, Souhaib Ben Taieb