Papers
POLITEX: Regret Bounds for Policy Iteration using Expert Prediction
Yasin Abbasi-Yadkori, Peter Bartlett, Kush Bhatia et al.
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures
Andrew Lawrence, Carl Henrik Ek, Neill Campbell
Lorentzian Distance Learning for Hyperbolic Representations
Marc Law, Renjie Liao, Jake Snell et al.
A Better k-means++ Algorithm via Local Search
Silvio Lattanzi, Christian Sohler
Safe Policy Improvement with Baseline Bootstrapping
Romain Laroche, Paul Trichelair, Remi Tachet Des Combes
Projection onto Minkowski Sums with Application to Constrained Learning
Joong-Ho Won, Jason Xu, Kenneth Lange
A Recurrent Neural Cascade-based Model for Continuous-Time Diffusion
Sylvain Lamprier
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
Alex Lamb, Jonathan Binas, Anirudh Goyal et al.
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits
Branislav Kveton, Csaba Szepesvari, Sharan Vaswani et al.
Making Decisions that Reduce Discriminatory Impacts
Matt Kusner, Chris Russell, Joshua Loftus et al.
A Large-Scale Study on Regularization and Normalization in GANs
Karol Kurach, Mario Lučić, Xiaohua Zhai et al.
Geometry and Symmetry in Short-and-Sparse Deconvolution
Han-Wen Kuo, Yenson Lau, Yuqian Zhang et al.
Loss Landscapes of Regularized Linear Autoencoders
Daniel Kunin, Jonathan Bloom, Aleksandrina Goeva et al.
Faster Algorithms for Binary Matrix Factorization
Ravi Kumar, Rina Panigrahy, Ali Rahimi et al.
Estimate Sequences for Variance-Reduced Stochastic Composite Optimization
Andrei Kulunchakov, Julien Mairal
On the Complexity of Approximating Wasserstein Barycenters
Alexey Kroshnin, Nazarii Tupitsa, Darina Dvinskikh et al.
Similarity of Neural Network Representations Revisited
Simon Kornblith, Mohammad Norouzi, Honglak Lee et al.
LIT: Learned Intermediate Representation Training for Model Compression
Animesh Koratana, Daniel Kang, Peter Bailis et al.
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
Wouter Kool, Herke Van Hoof, Max Welling
Robust Learning from Untrusted Sources
Nikola Konstantinov, Christoph Lampert
Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication
Anastasia Koloskova, Sebastian Stich, Martin Jaggi
POPQORN: Quantifying Robustness of Recurrent Neural Networks
Ching-Yun Ko, Zhaoyang Lyu, Lily Weng et al.
Guarantees for Spectral Clustering with Fairness Constraints
Matthäus Kleindessner, Samira Samadi, Pranjal Awasthi et al.
Fair k-Center Clustering for Data Summarization
Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern