Papers
Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples
Yixing Zhang, Xiuyuan Cheng, Galen Reeves
Convergence Properties of Stochastic Hypergradients
Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo
Corralling Stochastic Bandit Algorithms
Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri
Counterfactual Representation Learning with Balancing Weights
Serge Assaad, Shuxi Zeng, Chenyang Tao et al.
Couplings for Multinomial Hamiltonian Monte Carlo
Kai Xu, Tor Erlend Fjelde, Charles Sutton et al.
Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates
Sebastian Stich, Amirkeivan Mohtashami, Martin Jaggi
Curriculum Learning by Optimizing Learning Dynamics
Tianyi Zhou, Shengjie Wang, Jeff Bilmes
CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices
Valerii Likhosherstov, Jared Davis, Krzysztof Choromanski et al.
DAG-Structured Clustering by Nearest Neighbors
Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey et al.
Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns
Ziping Xu, Amirhossein Meisami, Ambuj Tewari
Deep Fourier Kernel for Self-Attentive Point Processes
Shixiang Zhu, Minghe Zhang, Ruyi Ding et al.
Deep Generative Missingness Pattern-Set Mixture Models
Sahra Ghalebikesabi, Rob Cornish, Chris Holmes et al.
Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond
Nina Vesseron, Ievgen Redko, Charlotte Laclau
Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems
Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar et al.
Deep Spectral Ranking
Ilkay Yildiz, Jennifer Dy, Deniz Erdogmus et al.
Density of States Estimation for Out of Distribution Detection
Warren Morningstar, Cusuh Ham, Andrew Gallagher et al.
Designing Transportable Experiments Under S-admissability
My Phan, David Arbour, Drew Dimmery et al.
Detection and Defense of Topological Adversarial Attacks on Graphs
Yingxue Zhang, Florence Regol, Soumyasundar Pal et al.
Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain
Takahiro Mimori, Keiko Sasada, Hirotaka Matsui et al.
Differentiable Causal Discovery Under Unmeasured Confounding
Rohit Bhattacharya, Tushar Nagarajan, Daniel Malinsky et al.
Differentiable Divergences Between Time Series
Mathieu Blondel, Arthur Mensch, Jean-Philippe Vert
Differentially Private Analysis on Graph Streams
Jalaj Upadhyay, Sarvagya Upadhyay, Raman Arora
Differentially Private Monotone Submodular Maximization Under Matroid and Knapsack Constraints
Omid Sadeghi, Maryam Fazel