Papers
Multi-Task Zipping via Layer-wise Neuron Sharing
Xiaoxi He, Zimu Zhou, Lothar Thiele
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise
Dan Hendrycks, Mantas Mazeika, Duncan Wilson et al.
Online Improper Learning with an Approximation Oracle
Elad Hazan, Wei Hu, Yuanzhi Li et al.
Theoretical guarantees for EM under misspecified Gaussian mixture models
Raaz Dwivedi, nhật Hồ, Koulik Khamaru et al.
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems
Mrinmaya Sachan, Kumar Avinava Dubey, Tom M. Mitchell et al.
Differential Privacy for Growing Databases
Rachel Cummings, Sara Krehbiel, Kevin A Lai et al.
Breaking the Span Assumption Yields Fast Finite-Sum Minimization
Robert Hannah, Yanli Liu, Daniel O'Connor et al.
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Kimin Lee, Kibok Lee, Honglak Lee et al.
Bayesian Nonparametric Spectral Estimation
Felipe Tobar
Stochastic Expectation Maximization with Variance Reduction
Jianfei Chen, Jun Zhu, Yee Whye Teh et al.
Conditional Adversarial Domain Adaptation
Mingsheng Long, ZHANGJIE CAO, Jianmin Wang et al.
Bipartite Stochastic Block Models with Tiny Clusters
Stefan Neumann
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network
Aditya Kusupati, Manish Singh, Kush Bhatia et al.
Towards Text Generation with Adversarially Learned Neural Outlines
Sandeep Subramanian, Sai Rajeswar Mudumba, Alessandro Sordoni et al.
Model-Agnostic Private Learning
Raef Bassily, Om Thakkar, Abhradeep Guha Thakurta
A Unified Framework for Extensive-Form Game Abstraction with Bounds
Christian Kroer, Tuomas Sandholm
Testing for Families of Distributions via the Fourier Transform
Clément L Canonne, Ilias Diakonikolas, Alistair Stewart
Adaptive Path-Integral Autoencoders: Representation Learning and Planning for Dynamical Systems
Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae et al.
Frequency-Domain Dynamic Pruning for Convolutional Neural Networks
Zhenhua Liu, Jizheng Xu, Xiulian Peng et al.
A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers
Omer Ben-Porat, Moshe Tennenholtz
Evidential Deep Learning to Quantify Classification Uncertainty
Murat Sensoy, Lance Kaplan, Melih Kandemir
Differentially Private Robust Low-Rank Approximation
Raman Arora, Vladimir braverman, Jalaj Upadhyay
Fast Similarity Search via Optimal Sparse Lifting
Wenye Li, Jingwei Mao, Yin Zhang et al.
Learning Safe Policies with Expert Guidance
Jessie Huang, Fa Wu, Doina Precup et al.
Efficient nonmyopic batch active search
Shali Jiang, Gustavo Malkomes, Matthew Abbott et al.