Papers
Insights on representational similarity in neural networks with canonical correlation
Ari Morcos, Maithra Raghu, Samy Bengio
Data Amplification: A Unified and Competitive Approach to Property Estimation
Yi Hao, Alon Orlitsky, Ananda Theertha Suresh et al.
DeepExposure: Learning to Expose Photos with Asynchronously Reinforced Adversarial Learning
Runsheng Yu, Wenyu Liu, Yasen Zhang et al.
HOGWILD!-Gibbs can be PanAccurate
Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti
Memory Replay GANs: Learning to Generate New Categories without Forgetting
Chenshen Wu, Luis Herranz, Xialei Liu et al.
Representation Learning for Treatment Effect Estimation from Observational Data
Liuyi Yao, Sheng Li, Yaliang Li et al.
Non-monotone Submodular Maximization in Exponentially Fewer Iterations
Eric Balkanski, Adam Breuer, Yaron Singer
Visualizing the Loss Landscape of Neural Nets
Hao Li, Zheng Xu, Gavin Taylor et al.
Clebsch–Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network
Risi Kondor, Zhen Lin, Shubhendu Trivedi
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences
Jeremias Knoblauch, Jack E Jewson, Theodoros Damoulas
Information-based Adaptive Stimulus Selection to Optimize Communication Efficiency in Brain-Computer Interfaces
Boyla Mainsah, Dmitry Kalika, Leslie Collins et al.
Mallows Models for Top-k Lists
Flavio Chierichetti, Anirban Dasgupta, Shahrzad Haddadan et al.
Training Neural Networks Using Features Replay
Zhouyuan Huo, Bin Gu, Heng Huang
Deep Structured Prediction with Nonlinear Output Transformations
Colin Graber, Ofer Meshi, Alexander Schwing
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking
Patrick Chen, Si Si, Yang Li et al.
On Neuronal Capacity
Pierre Baldi, Roman Vershynin
Diversity-Driven Exploration Strategy for Deep Reinforcement Learning
Zhang-Wei Hong, Tzu-Yun Shann, Shih-Yang Su et al.
Learning to Reason with Third Order Tensor Products
Imanol Schlag, Jürgen Schmidhuber
Differentially Private Contextual Linear Bandits
Roshan Shariff, Or Sheffet
Smoothed analysis of the low-rank approach for smooth semidefinite programs
Thomas Pumir, Samy Jelassi, Nicolas Boumal
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport
Lénaïc Chizat, Francis Bach
Co-teaching: Robust training of deep neural networks with extremely noisy labels
Bo Han, Quanming Yao, Xingrui Yu et al.
Predictive Approximate Bayesian Computation via Saddle Points
Yingxiang Yang, Bo Dai, Negar Kiyavash et al.
Computationally and statistically efficient learning of causal Bayes nets using path queries
Kevin Bello, Jean Honorio
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies
Alessandro Achille, Tom Eccles, Loic Matthey et al.