Jesse Read

Viterbi Classifier Chains for Multi-Dimensional Learning

2015 · viXra

Multi-dimensional classification (also known variously as multi-target, multi-objective, and multi-output classification) is the supervised learning problem where an instance is associated to qualitative discrete variables (a.k.a. labels), rather than with a single class, as in …

Low-latency multi-threaded ensemble learning for dynamic big data streams

2017

Real-time mining of evolving data streams involves new challenges when targeting today's application domains such as the Internet of the Things: increasing volume, velocity and volatility requires data to be processed on-the-fly with fast reaction …

Parameter-Efficient Distributional RL via Normalizing Flows and a Geometry-Aware Cramér Surrogate

2025 · ArXiv.org

Distributional Reinforcement Learning (DistRL) improves upon expectation-based methods by modeling full return distributions, but standard approaches often remain far from parsimonious. Categorical methods (e.g., C51) rely on fixed supports where parameter counts scale linearly with …