7.4k citations · 22.9k across the 86 of their papers we have counts for
5 papers · 1 filter
Learning unbiased features
Yujia Li, Kevin Swersky, Richard Zemel
A key element in transfer learning is representation learning; if representations can be developed that expose the relevant factors underlying the data, then new tasks and domains…
Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models
Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel
Inspired by recent advances in multimodal learning and machine translation, we introduce an encoder-decoder pipeline that learns (a): a multimodal joint embedding space with images…
Mean-Field Networks
Yujia Li, Richard Zemel
The mean field algorithm is a widely used approximate inference algorithm for graphical models whose exact inference is intractable. In each iteration of mean field, the approximat…
A Multiplicative Model for Learning Distributed Text-Based Attribute Representations
Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov
In this paper we propose a general framework for learning distributed representations of attributes: characteristics of text whose representations can be jointly learned with word…
Input Warping for Bayesian Optimization of Non-stationary Functions
Jasper Snoek, Kevin Swersky, Richard S. Zemel +1
Bayesian optimization has proven to be a highly effective methodology for the global optimization of unknown, expensive and multimodal functions. The ability to accurately model di…