Papers
4,122 papers found
An Eigenmodel for Dynamic Multilayer Networks
Joshua Daniel Loyal, Yuguo Chen
An Empirical Investigation of the Role of Pre-training in Lifelong Learning
Sanket Vaibhav Mehta, Darshan Patil, Sarath Chandar et al.
A New Look at Dynamic Regret for Non-Stationary Stochastic Bandits
Yasin Abbasi-Yadkori, András György, Nevena Lazić
An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization
Le Thi Khanh Hien, Duy Nhat Phan, Nicolas Gillis
An Inexact Augmented Lagrangian Algorithm for Training Leaky ReLU Neural Network with Group Sparsity
Wei Liu, Xin Liu, Xiaojun Chen
A Non-parametric View of FedAvg and FedProx:Beyond Stationary Points
Lili Su, Jiaming Xu, Pengkun Yang
A Novel Integer Linear Programming Approach for Global L0 Minimization
Diego Delle Donne, Matthieu Kowalski, Leo Liberti
A Parameter-Free Conditional Gradient Method for Composite Minimization under Hölder Condition
Masaru Ito, Zhaosong Lu, Chuan He
A PDE approach for regret bounds under partial monitoring
Erhan Bayraktar, Ibrahim Ekren, Xin Zhang
A Permutation-Free Kernel Independence Test
Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas
Approximate Post-Selective Inference for Regression with the Group LASSO
Snigdha Panigrahi, Peter W MacDonald, Daniel Kessler
Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search
Benjamin Moseley, Joshua R. Wang
A Randomized Subspace-based Approach for Dimensionality Reduction and Important Variable Selection
Di Bo, Hoon Hwangbo, Vinit Sharma et al.
A Relaxed Inertial Forward-Backward-Forward Algorithm for Solving Monotone Inclusions with Application to GANs
Radu I. Bot, Michael Sedlmayer, Phan Tu Vuong
A Rigorous Information-Theoretic Definition of Redundancy and Relevancy in Feature Selection Based on (Partial) Information Decomposition
Patricia Wollstadt, Sebastian Schmitt, Michael Wibral
A Scalable and Efficient Iterative Method for Copying Machine Learning Classifiers
Nahuel Statuto, Irene Unceta, Jordi Nin et al.
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren et al.
Asymptotics of Network Embeddings Learned via Subsampling
Andrew Davison, Morgane Austern
Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees
Hamid Reza Feyzmahdavian, Mikael Johansson
Atlas: Few-shot Learning with Retrieval Augmented Language Models
Gautier Izacard, Patrick Lewis, Maria Lomeli et al.
Attacks against Federated Learning Defense Systems and their Mitigation
Cody Lewis, Vijay Varadharajan, Nasimul Noman
Attribution-based Explanations that Provide Recourse Cannot be Robust
Hidde Fokkema, Rianne de Heide, Tim van Erven
Augmented Sparsifiers for Generalized Hypergraph Cuts
Nate Veldt, Austin R. Benson, Jon Kleinberg
Augmented Transfer Regression Learning with Semi-non-parametric Nuisance Models
Molei Liu, Yi Zhang, Katherine P. Liao et al.
A Unified Analysis of Multi-task Functional Linear Regression Models with Manifold Constraint and Composite Quadratic Penalty
Shiyuan He, Hanxuan Ye, Kejun He