Psychology TodayOpinion

Automating Away Entry-Level Learning

Observation is no substitute for participation. As automation replaces hands-on entry-level work, we limit learning and ...
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Supervised learning made easy: Real-world example explained

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its applications. Supervised learning is a type of Machine Learning which learns ...
GitHub

TRAPO: A Semi-Supervised Reinforcement Learning Framework for Boosting LLM Reasoning.

TraPO is a semi-supervised reinforcement learning framework that bridges unlabeled and labeled samples for training large reasoning models (LRMs). Built upon GRPO, TraPO leverages a small set of ...
VentureBeat

Google’s new AI training method helps small models tackle complex reasoning

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...
IEEE

Learning With Partial-Label and Unlabeled Data: Contrastive With Negative Example Separation

Abstract: Semi-Supervised Partial Label Learning (SSPLL) is an important branch of weakly supervised learning, where the data consists of both partial label examples and unlabeled ones. In SSPLL, the ...
IEEE

Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examples

Abstract: Semi-supervised learning (SSL) methods have shown promising results in solving many practical problems when only a few labels are available. The existing methods assume that the class ...
www.cs.utexas.edu

Raymond J. Mooney

B.S. in Computer Engineering, University of Illinois at Urbana/Champaign, 1983 M.S. in Computer Science, University of Illinois at Urbana/Champaign, 1985 See my invited talk at the EMNLP 2023 Big ...