Papers
4,122 papers found
Wasserstein Proximal Coordinate Gradient Algorithms
Rentian Yao, Xiaohui Chen, Yun Yang
White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?
Yaodong Yu, Sam Buchanan, Druv Pai et al.
Win: Weight-Decay-Integrated Nesterov Acceleration for Faster Network Training
Pan Zhou, Xingyu Xie, Zhouchen Lin et al.
Zeroth-order Stochastic Approximation Algorithms for DR-submodular Optimization
Yuefang Lian, Xiao Wang, Dachuan Xu et al.
Accelerated Primal-Dual Mirror Dynamics for Centralized and Distributed Constrained Convex Optimization Problems
You Zhao, Xiaofeng Liao, Xing He et al.
A Complete Characterization of Linear Estimators for Offline Policy Evaluation
Juan C. Perdomo, Akshay Krishnamurthy, Peter Bartlett et al.
A Continuous-time Stochastic Gradient Descent Method for Continuous Data
Kexin Jin, Jonas Latz, Chenguang Liu et al.
Adaptation Augmented Model-based Policy Optimization
Jian Shen, Hang Lai, Minghuan Liu et al.
Adaptation to the Range in K-Armed Bandits
Hédi Hadiji, Gilles Stoltz
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees
Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd
Adaptive Clustering Using Kernel Density Estimators
Ingo Steinwart, Bharath K. Sriperumbudur, Philipp Thomann
Adaptive Data Depth via Multi-Armed Bandits
Tavor Baharav, Tze Leung Lai
Adaptive False Discovery Rate Control with Privacy Guarantee
Xintao Xia, Zhanrui Cai
Adaptive Learning of Density Ratios in RKHS
Werner Zellinger, Stefan Kindermann, Sergei V. Pereverzyev
A First Look into the Carbon Footprint of Federated Learning
Xinchi Qiu, Titouan Parcollet, Javier Fernandez-Marques et al.
A Framework and Benchmark for Deep Batch Active Learning for Regression
David Holzmüller, Viktor Zaverkin, Johannes Kästner et al.
A General Learning Framework for Open Ad Hoc Teamwork Using Graph-based Policy Learning
Arrasy Rahman, Ignacio Carlucho, Niklas Höpner et al.
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates
Yann Fraboni, Richard Vidal, Laetitia Kameni et al.
A Group-Theoretic Approach to Computational Abstraction: Symmetry-Driven Hierarchical Clustering
Haizi Yu, Igor Mineyev, Lav R. Varshney
A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models
Minwoo Chae, Dongha Kim, Yongdai Kim et al.
A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees
Michael J. O'Neill, Stephen J. Wright
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics
Kamélia Daudel, Joe Benton, Yuyang Shi et al.
An Analysis of Robustness of Non-Lipschitz Networks
Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma et al.
An Annotated Graph Model with Differential Degree Heterogeneity for Directed Networks
Stefan Stein, Chenlei Leng