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AI Blogs
Graph-Aided Online Multi-Kernel Learning Authors: Pouya M. Ghari, Yanning Shen; 24(21):1−44, 2023. Abstract Multi-kernel learning (MKL) has gained popularity in function learning tasks. Unlike single kernel learning, which relies on a pre-selected kernel, MKL combines a dictionary of kernels to…
Content moderation is crucial for maintaining online safety and upholding the standards of websites and social media platforms. It protects users from inappropriate content and ensures their well-being in digital spaces. For advertisers, content moderation helps protect their brands from…
Policy Gradient Methods and the Nash Equilibrium in N-player General-sum Linear-quadratic Games Authors: Ben Hambly, Renyuan Xu, Huining Yang; Journal of Machine Learning Research, 24(139):1−56, 2023. Abstract This study focuses on the convergence of the natural policy gradient method to…
The success of generative AI applications in various industries has caught the attention of companies worldwide. These companies are interested in replicating and surpassing the achievements of their competitors or finding new and exciting use cases. To power their generative…
Bayesian Data Selection Eli N. Weinstein, Jeffrey W. Miller; 24(23):1−72, 2023. Abstract To gain insights into complex, high-dimensional data, it is important to identify features of the data that either match or do not match a given model of interest.…
Jump Interval-Learning for Individualized Decision Making with Continuous Treatments Authors: Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu; 24(140):1−92, 2023. Abstract This paper introduces jump interval-learning, a method for developing an individualized interval-valued decision rule (I2DR) that maximizes expected outcomes…
Discrete Variational Calculus for Accelerated Optimization Cédric M. Campos, Alejandro Mahillo, David Martín de Diego; 24(25):1−33, 2023. Abstract The field of machine learning has seen significant advancements in gradient-based optimization methods. A recent approach to studying these methods is through…
Optimal Convergence Rates for Distributed Nystroem Approximation Jian Li, Yong Liu, Weiping Wang; 24(141):1−39, 2023. Abstract The distributed kernel ridge regression (DKRR) has demonstrated significant potential in handling complex tasks. However, DKRR only relies on local samples, which may not…
The SKIM-FA Kernel: High-Dimensional Variable Selection and Nonlinear Interaction Discovery in Linear Time Authors: Raj Agrawal, Tamara Broderick; Published in 2023, 24(27):1−60. Abstract Identifying a small set of covariates associated with a target response and estimating their effects is a…
On Tilted Losses in Machine Learning: Theory and Applications Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith; 24(142):1−79, 2023. Abstract Exponential tilting is a technique commonly employed in statistics, probability, information theory, and optimization to introduce parametric distribution shifts. Despite…
