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UAI
1996
13 years 11 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
AAAI
2008
14 years 13 days ago
Learning to Connect Language and Perception
To truly understand language, an intelligent system must be able to connect words, phrases, and sentences to its perception of objects and events in the world. Current natural lan...
Raymond J. Mooney
CHI
2011
ACM
13 years 1 months ago
Playable data: characterizing the design space of game-y infographics
This work explores the intersection between infographics and games by examining how to embed meaningful visual analytic interactions into game mechanics that in turn impact user b...
Nicholas Diakopoulos, Funda Kivran-Swaine, Mor Naa...
ICML
2010
IEEE
13 years 11 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
AAAI
2008
14 years 13 days ago
Learning to Improve Earth Observation Flight Planning
This paper describes a method and system for integrating machine learning with planning and data visualization for the management of mobile sensors for Earth science investigation...
Robert A. Morris, Nikunj C. Oza, Leslie Keely, Eli...