Papers
Efficient Formal Safety Analysis of Neural Networks
Shiqi Wang, Kexin Pei, Justin Whitehouse et al.
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses
Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri et al.
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features
Mojmir Mutny, Andreas Krause
Efficient inference for time-varying behavior during learning
Nicholas A. Roy, Ji Hyun Bak, Athena Akrami et al.
Efficient Loss-Based Decoding on Graphs for Extreme Classification
Itay Evron, Edward Moroshko, Koby Crammer
Efficient Neural Network Robustness Certification with General Activation Functions
Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen et al.
Efficient nonmyopic batch active search
Shali Jiang, Gustavo Malkomes, Matthew Abbott et al.
Efficient online algorithms for fast-rate regret bounds under sparsity
Pierre Gaillard, Olivier Wintenberger
Efficient Online Portfolio with Logarithmic Regret
Haipeng Luo, Chen-Yu Wei, Kai Zheng
Efficient Projection onto the Perfect Phylogeny Model
Bei Jia, Surjyendu Ray, Sam Safavi et al.
Efficient Stochastic Gradient Hard Thresholding
Pan Zhou, Xiaotong Yuan, Jiashi Feng
Embedding Logical Queries on Knowledge Graphs
Will Hamilton, Payal Bajaj, Marinka Zitnik et al.
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited
Di Wang, Marco Gaboardi, Jinhui Xu
Empirical Risk Minimization Under Fairness Constraints
Michele Donini, Luca Oneto, Shai Ben-David et al.
End-to-End Differentiable Physics for Learning and Control
Filipe de Avila Belbute-Peres, Kevin Smith, Kelsey Allen et al.
End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems
Linfeng Zhang, Jiequn Han, Han Wang et al.
Enhancing the Accuracy and Fairness of Human Decision Making
Isabel Valera, Adish Singla, Manuel Gomez Rodriguez
Entropy and mutual information in models of deep neural networks
Marylou Gabrié, Andre Manoel, Clément Luneau et al.
Entropy Rate Estimation for Markov Chains with Large State Space
Yanjun Han, Jiantao Jiao, Chuan-Zheng Lee et al.
Equality of Opportunity in Classification: A Causal Approach
Junzhe Zhang, Elias Bareinboim
Escaping Saddle Points in Constrained Optimization
Aryan Mokhtari, Asuman Ozdaglar, Ali Jadbabaie
e-SNLI: Natural Language Inference with Natural Language Explanations
Oana-Maria Camburu, Tim Rocktäschel, Thomas Lukasiewicz et al.
Estimating Learnability in the Sublinear Data Regime
Weihao Kong, Gregory Valiant
Estimators for Multivariate Information Measures in General Probability Spaces
Arman Rahimzamani, Himanshu Asnani, Pramod Viswanath et al.
Evidential Deep Learning to Quantify Classification Uncertainty
Murat Sensoy, Lance Kaplan, Melih Kandemir