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Publication search results
found 67 matches
- 2024
- Pierre Alquier
:
User-friendly Introduction to PAC-Bayes Bounds. Found. Trends Mach. Learn. 17(2): 174-303 (2024) - Xuanyi Dong, David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys:
Automated Deep Learning: Neural Architecture Search Is Not the End. Found. Trends Mach. Learn. 17(5): 767-920 (2024) - David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys:
AutonoML: Towards an Integrated Framework for Autonomous Machine Learning. Found. Trends Mach. Learn. 17(4): 590-766 (2024) - Andrea Montanari, Subhabrata Sen:
A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists. Found. Trends Mach. Learn. 17(1): 1-173 (2024) - Drago Plecko, Elias Bareinboim:
Causal Fairness Analysis: A Causal Toolkit for Fair Machine Learning. Found. Trends Mach. Learn. 17(3): 304-589 (2024) - 2023
- Brandon Amos:
Tutorial on Amortized Optimization. Found. Trends Mach. Learn. 16(5): 592-732 (2023) - Anastasios N. Angelopoulos, Stephen Bates:
Conformal Prediction: A Gentle Introduction. Found. Trends Mach. Learn. 16(4): 494-591 (2023) - Nicolas Guigui, Nina Miolane, Xavier Pennec:
Introduction to Riemannian Geometry and Geometric Statistics: From Basic Theory to Implementation with Geomstats. Found. Trends Mach. Learn. 16(3): 329-493 (2023) - Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen:
Reinforcement Learning, Bit by Bit. Found. Trends Mach. Learn. 16(6): 733-865 (2023) - Thomas M. Moerland, Joost Broekens, Aske Plaat, Catholijn M. Jonker:
Model-based Reinforcement Learning: A Survey. Found. Trends Mach. Learn. 16(1): 1-118 (2023) - Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long:
Graph Neural Networks for Natural Language Processing: A Survey. Found. Trends Mach. Learn. 16(2): 119-328 (2023) - 2022
- Prashanth L. A., Michael C. Fu:
Risk-Sensitive Reinforcement Learning via Policy Gradient Search. Found. Trends Mach. Learn. 15(5): 537-693 (2022) - Oliver Y. Feng, Ramji Venkataramanan, Cynthia Rush, Richard J. Samworth:
A Unifying Tutorial on Approximate Message Passing. Found. Trends Mach. Learn. 15(4): 335-536 (2022) - Thomas Nedelec, Clément Calauzènes, Noureddine El Karoui, Vianney Perchet:
Learning in Repeated Auctions. Found. Trends Mach. Learn. 15(3): 176-334 (2022) - Ryan J. Tibshirani:
Divided Differences, Falling Factorials, and Discrete Splines: Another Look at Trend Filtering and Related Problems. Found. Trends Mach. Learn. 15(6): 694-846 (2022) - 2021
- Akshay Agrawal, Alnur Ali, Stephen P. Boyd:
Minimum-Distortion Embedding. Found. Trends Mach. Learn. 14(3): 211-378 (2021) - Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma:
Spectral Methods for Data Science: A Statistical Perspective. Found. Trends Mach. Learn. 14(5): 566-806 (2021) - Laurent Girin, Simon Leglaive, Xiaoyu Bie, Julien Diard, Thomas Hueber, Xavier Alameda-Pineda:
Dynamical Variational Autoencoders: A Comprehensive Review. Found. Trends Mach. Learn. 15(1-2): 1-175 (2021) - Sean B. Holden:
Machine Learning for Automated Theorem Proving: Learning to Solve SAT and QSAT. Found. Trends Mach. Learn. 14(6): 807-989 (2021) - Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - Jiani Liu, Ce Zhu, Zhen Long, Yipeng Liu:
Tensor Regression. Found. Trends Mach. Learn. 14(4): 379-565 (2021) - 2020
- Karsten M. Borgwardt, M. Elisabetta Ghisu, Felipe Llinares-López, Leslie O'Bray, Bastian Rieck:
Graph Kernels: State-of-the-Art and Future Challenges. Found. Trends Mach. Learn. 13(5-6) (2020) - Ljubisa Stankovic, Danilo P. Mandic, Milos Dakovic, Milos Brajovic, Bruno Scalzo, Shengxi Li, Anthony G. Constantinides:
Data Analytics on Graphs Part I: Graphs and Spectra on Graphs. Found. Trends Mach. Learn. 13(1): 1-157 (2020) - Ljubisa Stankovic, Danilo P. Mandic, Milos Dakovic, Milos Brajovic, Bruno Scalzo, Shengxi Li, Anthony G. Constantinides:
Data Analytics on Graphs Part II: Signals on Graphs. Found. Trends Mach. Learn. 13(2-3): 158-331 (2020) - Ljubisa Stankovic, Danilo P. Mandic, Milos Dakovic, Milos Brajovic, Bruno Scalzo, Shengxi Li, Anthony G. Constantinides:
Data Analytics on Graphs Part III: Machine Learning on Graphs, from Graph Topology to Applications. Found. Trends Mach. Learn. 13(4): 332-530 (2020) - 2019
- Majid Janzamin, Rong Ge, Jean Kossaifi, Anima Anandkumar:
Spectral Learning on Matrices and Tensors. Found. Trends Mach. Learn. 12(5-6): 393-536 (2019) - Diederik P. Kingma, Max Welling:
An Introduction to Variational Autoencoders. Found. Trends Mach. Learn. 12(4): 307-392 (2019) - Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön:
Elements of Sequential Monte Carlo. Found. Trends Mach. Learn. 12(3): 307-392 (2019) - Gabriel Peyré, Marco Cuturi:
Computational Optimal Transport. Found. Trends Mach. Learn. 11(5-6): 355-607 (2019) - Aleksandrs Slivkins:
Introduction to Multi-Armed Bandits. Found. Trends Mach. Learn. 12(1-2): 1-286 (2019)
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