6 citations · 26 across the 12 of their papers we have counts for
7 papers · 1 filter
Direct Acquisition Optimization for Low-Budget Active Learning
Zhuokai Zhao, Yibo Jiang, Yuxin Chen
Active Learning (AL) has gained prominence in integrating data-intensive machine learning (ML) models into domains with limited labeled data. However, its effectiveness diminishes…
Uncovering Meanings of Embeddings via Partial Orthogonality
Yibo Jiang, Bryon Aragam, Victor Veitch
Machine learning tools often rely on embedding text as vectors of real numbers. In this paper, we study how the semantic structure of language is encoded in the algebraic structure…
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints
Chaoqi Wang, Yibo Jiang, Chenghao Yang +2
The increasing capabilities of large language models (LLMs) raise opportunities for artificial general intelligence but concurrently amplify safety concerns, such as potential misu…
Invariant and Transportable Representations for Anti-Causal Domain Shifts
Yibo Jiang, Victor Veitch
Real-world classification problems must contend with domain shift, the (potential) mismatch between the domain where a model is deployed and the domain(s) where the training data w…
Associative Memory in Iterated Overparameterized Sigmoid Autoencoders
Yibo Jiang, Cengiz Pehlevan
Recent work showed that overparameterized autoencoders can be trained to implement associative memory via iterative maps, when the trained input-output Jacobian of the network has…
Meta-Learning to Cluster
Yibo Jiang, Nakul Verma
Clustering is one of the most fundamental and wide-spread techniques in exploratory data analysis. Yet, the basic approach to clustering has not really changed: a practitioner hand…
Model-Agnostic Meta-Learning using Runge-Kutta Methods
Daniel Jiwoong Im, Yibo Jiang, Nakul Verma
Meta-learning has emerged as an important framework for learning new tasks from just a few examples. The success of any meta-learning model depends on (i) its fast adaptation to ne…