Papers
1,396 papers found
From Sampling to Optimization on Discrete Domains with Applications to Determinant Maximization
Nima Anari, Thuy-Duong Vuong
Gardner formula for Ising perceptron models at small densities
Erwin Bolthausen, Shuta Nakajima, Nike Sun et al.
Generalization Bounds for Data-Driven Numerical Linear Algebra
Peter Bartlett, Piotr Indyk, Tal Wagner
Generalization Bounds via Convex Analysis
Gabor Lugosi, Gergely Neu
Hardness of Maximum Likelihood Learning of DPPs
Elena Grigorescu, Brendan Juba, Karl Wimmer et al.
Hierarchical Clustering in Graph Streams: Single-Pass Algorithms and Space Lower Bounds
Sepehr Assadi, Vaggos Chatziafratis, Jakub \Lącki et al.
High-Dimensional Projection Pursuit: Outer Bounds and Applications to Interpolation in Neural Networks
Kangjie Zhou, Andrea Montanari
Horizon-Free Reinforcement Learning in Polynomial Time: the Power of Stationary Policies
Zihan Zhang, Xiangyang Ji, Simon Du
How catastrophic can catastrophic forgetting be in linear regression?
Itay Evron, Edward Moroshko, Rachel Ward et al.
Improved analysis for a proximal algorithm for sampling
Yongxin Chen, Sinho Chewi, Adil Salim et al.
Improved Parallel Algorithm for Minimum Cost Submodular Cover Problem
Yingli Ran, Zhao Zhang, Shaojie Tang
Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm
Meena Jagadeesan, Ilya Razenshteyn, Suriya Gunasekar
Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation
Loucas Pillaud Vivien, Julien Reygner, Nicolas Flammarion
Lattice-Based Methods Surpass Sum-of-Squares in Clustering
Ilias Zadik, Min Jae Song, Alexander S Wein et al.
Learning a Single Neuron with Adversarial Label Noise via Gradient Descent
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos et al.
Learning GMMs with Nearly Optimal Robustness Guarantees
Allen Liu, Ankur Moitra
Learning Low Degree Hypergraphs
Eric Balkanski, Oussama Hanguir, Shatian Wang
Learning to Control Linear Systems can be Hard
Anastasios Tsiamis, Ingvar M Ziemann, Manfred Morari et al.
Learning with metric losses
Dan Tsir Cohen, Aryeh Kontorovich
Low-Degree Multicalibration
Parikshit Gopalan, Michael P Kim, Mihir A Singhal et al.
Making SGD Parameter-Free
Yair Carmon, Oliver Hinder
Mean-field nonparametric estimation of interacting particle systems
Rentian Yao, Xiaohui Chen, Yun Yang
Memorize to generalize: on the necessity of interpolation in high dimensional linear regression
Chen Cheng, John Duchi, Rohith Kuditipudi