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Publication search results
found 216 matches
- 2020
- Wouter Kool, Herke van Hoof, Max Welling:
Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement. J. Mach. Learn. Res. 21: 47:1-47:36 (2020) - Hao Yu, Michael J. Neely:
A Low Complexity Algorithm with O(√T) Regret and O(1) Constraint Violations for Online Convex Optimization with Long Term Constraints. J. Mach. Learn. Res. 21: 1:1-1:24 (2020) - Hang Yu, Songwei Wu, Luyin Xin, Justin Dauwels:
Fast Bayesian Inference of Sparse Networks with Automatic Sparsity Determination. J. Mach. Learn. Res. 21: 124:1-124:54 (2020) - Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Sundar Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang:
GluonTS: Probabilistic and Neural Time Series Modeling in Python. J. Mach. Learn. Res. 21: 116:1-116:6 (2020) - Pan Li, Niao He, Olgica Milenkovic:
Quadratic Decomposable Submodular Function Minimization: Theory and Practice. J. Mach. Learn. Res. 21: 106:1-106:49 (2020) - Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
A Unified Framework for Structured Graph Learning via Spectral Constraints. J. Mach. Learn. Res. 21: 22:1-22:60 (2020) - Huan Li, Zhouchen Lin:
On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent. J. Mach. Learn. Res. 21: 33:1-33:45 (2020) - Di Wang, Marco Gaboardi
, Adam D. Smith, Jinhui Xu:
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy. J. Mach. Learn. Res. 21: 200:1-200:39 (2020) - Yu Wang, Siqi Wu, Bin Yu:
Unique Sharp Local Minimum in L1-minimization Complete Dictionary Learning. J. Mach. Learn. Res. 21: 63:1-63:52 (2020) - Emmanuel Abbe, Sanjeev R. Kulkarni, Eun Jee Lee:
Generalized Nonbacktracking Bounds on the Influence. J. Mach. Learn. Res. 21: 31:1-31:36 (2020) - Devanshu Agrawal, Theodore Papamarkou
Wide Neural Networks with Bottlenecks are Deep Gaussian Processes. J. Mach. Learn. Res. 21: 175:1-175:66 (2020) - Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Contextual Explanation Networks. J. Mach. Learn. Res. 21: 194:1-194:44 (2020) - Pragnya Alatur, Kfir Y. Levy, Andreas Krause:
Multi-Player Bandits: The Adversarial Case. J. Mach. Learn. Res. 21: 77:1-77:23 (2020) - Edesio Alcobaça, Felipe Siqueira, Adriano Rivolli, Luís Paulo F. Garcia, Jefferson Tales Oliva, André C. P. L. F. de Carvalho:
MFE: Towards reproducible meta-feature extraction. J. Mach. Learn. Res. 21: 111:1-111:5 (2020) - Israel Almodóvar-Rivera, Ranjan Maitra:
Kernel-estimated Nonparametric Overlap-Based Syncytial Clustering. J. Mach. Learn. Res. 21: 122:1-122:54 (2020) - Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg:
Kymatio: Scattering Transforms in Python. J. Mach. Learn. Res. 21: 60:1-60:6 (2020) - Robin Anil, Gökhan Çapan, Isabel Drost-Fromm, Ted Dunning, Ellen Friedman, Trevor Grant, Shannon Quinn, Paritosh Ranjan, Sebastian Schelter, Özgür Yilmazel:
Apache Mahout: Machine Learning on Distributed Dataflow Systems. J. Mach. Learn. Res. 21: 127:1-127:6 (2020) - Oleg Arenz
Trust-Region Variational Inference with Gaussian Mixture Models. J. Mach. Learn. Res. 21: 163:1-163:60 (2020) - Ery Arias-Castro, Adel Javanmard, Bruno Pelletier:
Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning. J. Mach. Learn. Res. 21: 15:1-15:37 (2020) - Sercan Ömer Arik, Tomas Pfister:
ProtoAttend: Attention-Based Prototypical Learning. J. Mach. Learn. Res. 21: 210:1-210:35 (2020) - Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models. J. Mach. Learn. Res. 21: 130:1-130:6 (2020) - Amir-Reza Asadi, Emmanuel Abbe:
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks. J. Mach. Learn. Res. 21: 139:1-139:32 (2020) - Morteza Ashraphijuo, Xiaodong Wang:
Union of Low-Rank Tensor Spaces: Clustering and Completion. J. Mach. Learn. Res. 21: 69:1-69:36 (2020) - Romain Azaïs
The weight function in the subtree kernel is decisive. J. Mach. Learn. Res. 21: 67:1-67:36 (2020) - Davide Bacciu, Federico Errica
Probabilistic Learning on Graphs via Contextual Architectures. J. Mach. Learn. Res. 21: 134:1-134:39 (2020) - Emmanuel Bacry, Martin Bompaire, Stéphane Gaïffas, Jean-François Muzy:
Sparse and low-rank multivariate Hawkes processes. J. Mach. Learn. Res. 21: 50:1-50:32 (2020) - Eugenio Bargiacchi, Diederik M. Roijers, Ann Nowé:
AI-Toolbox: A C++ library for Reinforcement Learning and Planning (with Python Bindings). J. Mach. Learn. Res. 21: 102:1-102:12 (2020) - Simon Bartels, Philipp Hennig:
Conjugate Gradients for Kernel Machines. J. Mach. Learn. Res. 21: 55:1-55:42 (2020) - Raef Bassily, Kobbi Nissim, Uri Stemmer, Abhradeep Thakurta:
Practical Locally Private Heavy Hitters. J. Mach. Learn. Res. 21: 16:1-16:42 (2020) - Ayoub Belhadji, Rémi Bardenet, Pierre Chainais:
A determinantal point process for column subset selection. J. Mach. Learn. Res. 21: 197:1-197:62 (2020)
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