Papers
A Contraction Approach to Model-based Reinforcement Learning
Ting-Han Fan, Peter Ramadge
Active Learning under Label Shift
Eric Zhao, Anqi Liu, Animashree Anandkumar et al.
Active Learning with Maximum Margin Sparse Gaussian Processes
Weishi Shi, Qi Yu
Active Online Learning with Hidden Shifting Domains
Yining Chen, Haipeng Luo, Tengyu Ma et al.
Adaptive Approximate Policy Iteration
Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori et al.
Adaptive Sampling for Fast Constrained Maximization of Submodular Functions
Francesco Quinzan, Vanja Doskoc, Andreas Göbel et al.
Adaptive wavelet pooling for convolutional neural networks
Moritz Wolter, Jochen Garcke
A Deterministic Streaming Sketch for Ridge Regression
Benwei Shi, Jeff Phillips
Adversarially Robust Estimate and Risk Analysis in Linear Regression
Yue Xing, Ruizhi Zhang, Guang Cheng
A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks
Zhiqi Bu, Shiyun Xu, Kan Chen
A Fast and Robust Method for Global Topological Functional Optimization
Yitzchak Solomon, Alexander Wagner, Paul Bendich
Aggregating Incomplete and Noisy Rankings
Dimitris Fotakis, Alkis Kalavasis, Konstantinos Stavropoulos
A Hybrid Approximation to the Marginal Likelihood
Eric Chuu, Debdeep Pati, Anirban Bhattacharya
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces
Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta et al.
Algorithms for Fairness in Sequential Decision Making
Min Wen, Osbert Bastani, Ufuk Topcu
Aligning Time Series on Incomparable Spaces
Samuel Cohen, Giulia Luise, Alexander Terenin et al.
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets
Gauthier Gidel, David Balduzzi, Wojciech Czarnecki et al.
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!
Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi et al.
All of the Fairness for Edge Prediction with Optimal Transport
Charlotte Laclau, Ievgen Redko, Manvi Choudhary et al.
Alternating Direction Method of Multipliers for Quantization
Tianjian Huang, Prajwal Singhania, Maziar Sanjabi et al.
Amortized Bayesian Prototype Meta-learning: A New Probabilistic Meta-learning Approach to Few-shot Image Classification
Zhuo Sun, Jijie Wu, Xiaoxu Li et al.
An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo
Matthew Hoffman, Alexey Radul, Pavel Sountsov
An Analysis of LIME for Text Data
Dina Mardaoui, Damien Garreau
An Analysis of the Adaptation Speed of Causal Models
Rémi Le Priol, Reza Babanezhad, Yoshua Bengio et al.
Anderson acceleration of coordinate descent
Quentin Bertrand, Mathurin Massias