Papers
4,025 papers found
Database Alignment with Gaussian Features
Osman E. Dai, Daniel Cullina, Negar Kiyavash
Data-dependent compression of random features for large-scale kernel approximation
Raj Agrawal, Trevor Campbell, Jonathan Huggins et al.
Data-Driven Approach to Multiple-Source Domain Adaptation
Petar Stojanov, Mingming Gong, Jaime Carbonell et al.
Decentralized Gradient Tracking for Continuous DR-Submodular Maximization
Jiahao Xie, Chao Zhang, Zebang Shen et al.
Deep learning with differential Gaussian process flows
Pashupati Hegde, Markus Heinonen, Harri Lähdesmäki et al.
Deep Neural Networks Learn Non-Smooth Functions Effectively
Masaaki Imaizumi, Kenji Fukumizu
Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex
Hongyang Zhang, Junru Shao, Ruslan Salakhutdinov
Deep Switch Networks for Generating Discrete Data and Language
Payam Delgosha, Naveen Goela
Deep Topic Models for Multi-label Learning
Rajat Panda, Ankit Pensia, Nikhil Mehta et al.
Defending against Whitebox Adversarial Attacks via Randomized Discretization
Yuchen Zhang, Percy Liang
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
Dhruv Malik, Ashwin Pananjady, Kush Bhatia et al.
Designing Optimal Binary Rating Systems
Nikhil Garg, Ramesh Johari
Detection of Planted Solutions for Flat Satisfiability Problems
Quentin Berthet, Jordan Ellenberg
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference
Mike Wu, Noah Goodman, Stefano Ermon
Differentially Private Online Submodular Minimization
Adrian Rivera Cardoso, Rachel Cummings
Direct Acceleration of SAGA using Sampled Negative Momentum
Kaiwen Zhou, Qinghua Ding, Fanhua Shang et al.
Distilling Policy Distillation
Wojciech M. Czarnecki, Razvan Pascanu, Simon Osindero et al.
Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning
Bo Liu, Xiao-Tong Yuan, Lezi Wang et al.
Distributed Maximization of "Submodular plus Diversity" Functions for Multi-label Feature Selection on Huge Datasets
Mehrdad Ghadiri, Mark Schmidt
Distributionally Robust Submodular Maximization
Matthew Staib, Bryan Wilder, Stefanie Jegelka
Distributional reinforcement learning with linear function approximation
Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro et al.
Does data interpolation contradict statistical optimality?
Mikhail Belkin, Alexander Rakhlin, Alexandre B. Tsybakov
Domain-Size Aware Markov Logic Networks
Happy Mittal, Ayush Bhardwaj, Vibhav Gogate et al.
Doubly Semi-Implicit Variational Inference
Dmitry Molchanov, Valery Kharitonov, Artem Sobolev et al.
Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function
Wojciech Tarnowski, Piotr Warchoł, Stanisław Jastrzȩbski et al.