Papers
4,122 papers found
Model-based Causal Discovery for Zero-Inflated Count Data
Junsouk Choi, Yang Ni
Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity
Kaiqing Zhang, Sham M. Kakade, Tamer Basar et al.
Modular Regression: Improving Linear Models by Incorporating Auxiliary Data
Ying Jin, Dominik Rothenhäusler
Monotonic Alpha-divergence Minimisation for Variational Inference
Kamélia Daudel, Randal Douc, François Roueff
Multi-Consensus Decentralized Accelerated Gradient Descent
Haishan Ye, Luo Luo, Ziang Zhou et al.
Multilevel CNNs for Parametric PDEs
Cosmas Heiß, Ingo Gühring, Martin Eigel
Multiplayer Performative Prediction: Learning in Decision-Dependent Games
Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy et al.
Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices
Doudou Zhou, Tianxi Cai, Junwei Lu
Multivariate Soft Rank via Entropy-Regularized Optimal Transport: Sample Efficiency and Generative Modeling
Shoaib Bin Masud, Matthew Werenski, James M. Murphy et al.
Multi-view Collaborative Gaussian Process Dynamical Systems
Shiliang Sun, Jingjing Fei, Jing Zhao et al.
MultiZoo and MultiBench: A Standardized Toolkit for Multimodal Deep Learning
Paul Pu Liang, Yiwei Lyu, Xiang Fan et al.
Naive regression requires weaker assumptions than factor models to adjust for multiple cause confounding
Justin Grimmer, Dean Knox, Brandon Stewart
Nearest Neighbor Dirichlet Mixtures
Shounak Chattopadhyay, Antik Chakraborty, David B. Dunson
Near-Optimal Weighted Matrix Completion
Oscar López
Necessary and Sufficient Conditions for Inverse Reinforcement Learning of Bayesian Stopping Time Problems
Kunal Pattanayak, Vikram Krishnamurthy
Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data
Shaowu Pan, Steven L. Brunton, J. Nathan Kutz
Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs
Nikola Kovachki, Zongyi Li, Burigede Liu et al.
Neural Q-learning for solving PDEs
Samuel N. Cohen, Deqing Jiang, Justin Sirignano
Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research
Jorg Bornschein, Alexandre Galashov, Ross Hemsley et al.
Non-Asymptotic Guarantees for Robust Statistical Learning under Infinite Variance Assumption
Lihu Xu, Fang Yao, Qiuran Yao et al.
Non-stationary Online Learning with Memory and Non-stochastic Control
Peng Zhao, Yu-Hu Yan, Yu-Xiang Wang et al.
Off-Policy Actor-Critic with Emphatic Weightings
Eric Graves, Ehsan Imani, Raksha Kumaraswamy et al.
On Batch Teaching Without Collusion
Shaun Fallat, David Kirkpatrick, Hans U. Simon et al.
On Biased Compression for Distributed Learning
Aleksandr Beznosikov, Samuel Horváth, Peter Richtárik et al.
On Distance and Kernel Measures of Conditional Dependence
Tianhong Sheng, Bharath K. Sriperumbudur