Papers
4,122 papers found
Convergence Guarantees for the Good-Turing Estimator
Amichai Painsky
Convergence Rates for Gaussian Mixtures of Experts
Nhat Ho, Chiao-Yu Yang, Michael I. Jordan
d3rlpy: An Offline Deep Reinforcement Learning Library
Takuma Seno, Michita Imai
Darts: User-Friendly Modern Machine Learning for Time Series
Julien Herzen, Francesco Lässig, Samuele Giuliano Piazzetta et al.
Data-Derived Weak Universal Consistency
Narayana Santhanam, Venkatachalam Anantharam, Wojciech Szpankowski
Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions
Shaogao Lv, Heng Lian
Decimated Framelet System on Graphs and Fast G-Framelet Transforms
Xuebin Zheng, Bingxin Zhou, Yu Guang Wang et al.
Deepchecks: A Library for Testing and Validating Machine Learning Models and Data
Shir Chorev, Philip Tannor, Dan Ben Israel et al.
Deep Learning in Target Space
Michael Fairbank, Spyridon Samothrakis, Luca Citi
Deep Limits and a Cut-Off Phenomenon for Neural Networks
Benny Avelin, Anders Karlsson
Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons
Shijun Zhang, Zuowei Shen, Haizhao Yang
Dependent randomized rounding for clustering and partition systems with knapsack constraints
David G. Harris, Thomas Pensyl, Aravind Srinivasan et al.
Depth separation beyond radial functions
Luca Venturi, Samy Jelassi, Tristan Ozuch et al.
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother
Adrien Corenflos, Nicolas Chopin, Simo Särkkä
Detecting Latent Communities in Network Formation Models
Shujie Ma, Liangjun Su, Yichong Zhang
D-GCCA: Decomposition-based Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data
Hai Shu, Zhe Qu, Hongtu Zhu
Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior
Rajarshi Guhaniyogi, Cheng Li, Terrance D. Savitsky et al.
Distributed Bootstrap for Simultaneous Inference Under High Dimensionality
Yang Yu, Shih-Kang Chao, Guang Cheng
Distributed Learning of Finite Gaussian Mixtures
Qiong Zhang, Jiahua Chen
Distributed Stochastic Gradient Descent: Nonconvexity, Nonsmoothness, and Convergence to Local Minima
Brian Swenson, Ryan Murray, H. Vincent Poor et al.
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression
Domagoj Cevid, Loris Michel, Jeffrey Näf et al.
DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python
Philipp Bach, Victor Chernozhukov, Malte S. Kurz et al.
Double Spike Dirichlet Priors for Structured Weighting
Huiming Lin, Meng Li
Early Stopping for Iterative Regularization with General Loss Functions
Ting Hu, Yunwen Lei
Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits
Lilian Besson, Emilie Kaufmann, Odalric-Ambrym Maillard et al.