Papers
Entropy Weighted Power k-Means Clustering
Saptarshi Chakraborty, Debolina Paul, Swagatam Das et al.
Equalized odds postprocessing under imperfect group information
Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions
Kamiar Rahnama Rad, Wenda Zhou, Arian Maleki
Explaining the Explainer: A First Theoretical Analysis of LIME
Damien Garreau, Ulrike Luxburg
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation
Shuhang Chen, Adithya Devraj, Ana Busic et al.
Expressiveness and Learning of Hidden Quantum Markov Models
Sandesh Adhikary, Siddarth Srinivasan, Geoff Gordon et al.
Fair Correlation Clustering
Sara Ahmadian, Alessandro Epasto, Ravi Kumar et al.
Fair Decisions Despite Imperfect Predictions
Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schölkopf et al.
Fairness Evaluation in Presence of Biased Noisy Labels
Riccardo Fogliato, Alexandra Chouldechova, Max G’Sell
Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter
Wenshuo Guo, Nhat Ho, Michael Jordan
Fast and Accurate Ranking Regression
Ilkay Yildiz, Jennifer Dy, Deniz Erdogmus et al.
Fast and Bayes-consistent nearest neighbors
Klim Efremenko, Aryeh Kontorovich, Moshe Noivirt
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation
Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji) et al.
Fast Markov chain Monte Carlo algorithms via Lie groups
Steve Huntsman
Fast Noise Removal for k-Means Clustering
Sungjin Im, Mahshid Montazer Qaem, Benjamin Moseley et al.
Feature relevance quantification in explainable AI: A causal problem
Dominik Janzing, Lenon Minorics, Patrick Bloebaum
Federated Heavy Hitters Discovery with Differential Privacy
Wennan Zhu, Peter Kairouz, Brendan McMahan et al.
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani et al.
Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training
Fangda Gu, Armin Askari, Laurent El Ghaoui
Finite-Time Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation
Jun Sun, Gang Wang, Georgios B. Giannakis et al.
Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning
Gang Wang, Georgios B. Giannakis
Fixed-confidence guarantees for Bayesian best-arm identification
Xuedong Shang, Rianne Heide, Pierre Menard et al.
Flexible distribution-free conditional predictive bands using density estimators
Rafael Izbicki, Gilson Shimizu, Rafael Stern
Formal Limitations on the Measurement of Mutual Information
David McAllester, Karl Stratos