conftrace_

ICML 2018

621 papers

Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data

Amjad Almahairi, Sai Rajeshwar, Alessandro Sordoni, Philip Bachman, Aaron Courville

Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits

Zeyuan Allen-Zhu, Sébastien Bubeck, Yuanzhi Li

Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization

Zeyuan Allen-Zhu

Differentially Private Identity and Equivalence Testing of Discrete Distributions

Maryam Aliakbarpour, Ilias Diakonikolas, Ronitt Rubinfeld

Fixing a Broken ELBO

Alexander Alemi, Ben Poole, Ian Fischer, Joshua Dillon, Rif A. Saurous

Information Theoretic Guarantees for Empirical Risk Minimization with Applications to Model Selection and Large-Scale Optimization

Ibrahim Alabdulmohsin

AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning

Ahmed Alaa, Mihaela Schaar

Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design

Ahmed Alaa, Mihaela Schaar

oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis

Samuel K. Ainsworth, Nicholas J. Foti, Adrian K. C. Lee, Emily B. Fox

Bucket Renormalization for Approximate Inference

Sungsoo Ahn, Michael Chertkov, Adrian Weller, Jinwoo Shin

Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy

Shipra Agrawal, Morteza Zadimoghaddam, Vahab Mirrokni

Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models

Raj Agrawal, Caroline Uhler, Tamara Broderick

MISSION: Ultra Large-Scale Feature Selection using Count-Sketches

Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava

Accelerated Spectral Ranking

Arpit Agarwal, Prathamesh Patil, Shivani Agarwal

A Reductions Approach to Fair Classification

Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna Wallach

Discovering Interpretable Representations for Both Deep Generative and Discriminative Models

Tameem Adel, Zoubin Ghahramani, Adrian Weller

Learning Representations and Generative Models for 3D Point Clouds

Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, Leonidas Guibas

INSPECTRE: Privately Estimating the Unseen

Jayadev Acharya, Gautam Kamath, Ziteng Sun, Huanyu Zhang

Policy and Value Transfer in Lifelong Reinforcement Learning

David Abel, Yuu Jinnai, Sophie Yue Guo, George Konidaris, Michael Littman

State Abstractions for Lifelong Reinforcement Learning

David Abel, Dilip Arumugam, Lucas Lehnert, Michael Littman

Improved Regret Bounds for Thompson Sampling in Linear Quadratic Control Problems

Marc Abeille, Alessandro Lazaric