Papers
4,122 papers found
Riemannian Bilevel Optimization
Jiaxiang Li, Shiqian Ma
Robust Point Matching with Distance Profiles
YoonHaeng Hur, Yuehaw Khoo
Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens
Amirreza Neshaei Moghaddam, Alex Olshevsky, Bahman Gharesifard
Sampling and Estimation on Manifolds using the Langevin Diffusion
Karthik Bharath, Alexander Lewis, Akash Sharma et al.
Scalable and Adaptive Variational Bayes Methods for Hawkes Processes
Deborah Sulem, Vincent Rivoirard, Judith Rousseau
Scaling Capability in Token Space: An Analysis of Large Vision Language Model
Tenghui Li, Guoxu Zhou, Xuyang Zhao et al.
Scaling Data-Constrained Language Models
Niklas Muennighoff, Alexander M. Rush, Boaz Barak et al.
Scaling ResNets in the Large-depth Regime
Pierre Marion, Adeline Fermanian, Gérard Biau et al.
Score-Aware Policy-Gradient and Performance Guarantees using Local Lyapunov Stability
Céline Comte, Matthieu Jonckheere, Jaron Sanders et al.
Score-based Causal Representation Learning: Linear and General Transformations
Burak Varici, Emre Acartürk, Karthikeyan Shanmugam et al.
Score-Based Diffusion Models in Function Space
Jae Hyun Lim, Nikola B. Kovachki, Ricardo Baptista et al.
Second-order Information Promotes Mini-Batch Robustness in Variance-Reduced Gradients
Sachin Garg, Albert S. Berahas, Michał Dereziński
Selective Inference with Distributed Data
Sifan Liu, Snigdha Panigrahi
Sharp Bounds for Sequential Federated Learning on Heterogeneous Data
Yipeng Li, Xinchen Lyu
Simplex Constrained Sparse Optimization via Tail Screening
Peng Chen, Jin Zhu, Junxian Zhu et al.
Sketching in High-Dimensional Regression With Big Data Using Gaussian Scale Mixture Priors
Rajarshi Guhaniyogi, Aaron Wolfe Scheffler
skglm: Improving scikit-learn for Regularized Generalized Linear Models
Badr Moufad, Pierre-Antoine Bannier, Quentin Bertrand et al.
Sliced-Wasserstein Distances and Flows on Cartan-Hadamard Manifolds
Clément Bonet, Lucas Drumetz, Nicolas Courty
Sparse Semiparametric Discriminant Analysis for High-dimensional Zero-inflated Data
Hee Cheol Chung, Yang Ni, Irina Gaynanova
Sparse SVM with Hard-Margin Loss: a Newton-Augmented Lagrangian Method in Reduced Dimensions
Penghe Zhang, Naihua Xiu, Hou-Duo Qi
Stabilizing Sharpness-Aware Minimization Through A Simple Renormalization Strategy
Chengli Tan, Jiangshe Zhang, Junmin Liu et al.
Stable learning using spiking neural networks equipped with affine encoders and decoders
A. Martina Neuman, Dominik Dold, Philipp Christian Petersen
Statistical field theory for Markov decision processes under uncertainty
George Stamatescu
Statistical Inference of Random Graphs With a Surrogate Likelihood Function
Dingbo Wu, Fangzheng Xie