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Foundations and Trends in Machine Learning - ResearchHub

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Journal

Foundations and Trends in Machine Learning

1935-8237 · Emerald

75 verified public works

Browse all journals →

Bayesian quadrature

2026 · 0 citations

A tutorial on learning from preferences and choices with Gaussian processes

2026 · 0 citations

Continual Learning as Computationally Constrained Reinforcement Learning

2025 · 0 citations

A Tutorial on Meta-Reinforcement Learning

2025 · 0 citations

Generalization Bounds: Perspectives from Information Theory and PAC-Bayes

2025 · 0 citations

Hyperparameter Optimization in Machine Learning

2025 · 0 citations

An Introduction to Deep Survival Analysis Models for Predicting Time-to-Event Outcomes

2024 · 0 citations

Automated Deep Learning: Neural Architecture Search Is Not the End

2024 · 0 citations

AutonoML: Towards an Integrated Framework for Autonomous Machine Learning

2024 · 0 citations

Causal Fairness Analysis: A Causal Toolkit for Fair Machine Learning

2024 · 0 citations

User-friendly Introduction to PAC-Bayes Bounds

2024 · 0 citations

A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists

2024 · 0 citations

Reinforcement Learning, Bit by Bit

2023 · 0 citations

Tutorial on Amortized Optimization

2023 · 0 citations

Conformal Prediction: A Gentle Introduction

2023 · 0 citations

Introduction to Riemannian Geometry and Geometric Statistics: From Basic Theory to Implementation with Geomstats

2023 · 0 citations

Graph Neural Networks for Natural Language Processing: A Survey

2023 · 0 citations

Model-based Reinforcement Learning: A Survey

2023 · 0 citations

Divided Differences, Falling Factorials, and Discrete Splines

2022 · 0 citations

Risk-Sensitive Reinforcement Learning via Policy Gradient Search

2022 · 0 citations

A Unifying Tutorial on Approximate Message Passing

2022 · 0 citations

Learning in Repeated Auctions

2022 · 0 citations

Dynamical Variational Autoencoders: A Comprehensive Review

2022 · 0 citations

Machine Learning for Automated Theorem Proving: Learning to Solve SAT and QSAT

2021 · 0 citations

Spectral Methods for Data Science: A Statistical Perspective

2021 · 0 citations

Tensor Regression

2021 · 0 citations

Minimum-Distortion Embedding

2021 · 0 citations

Advances and Open Problems in Federated Learning

2021 · 0 citations

Graph Kernels

2020 · 0 citations

Data Analytics on Graphs Part II: Signals on Graphs

2020 · 0 citations

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