Machine Learning & Data Analytics

We evaluated the behaviors by having children play a language-based game twice, once with a flexible host and once with an inflexible host that did not have access to the behaviors.

We examine the particular problem of identifying when each child playing an interactive game in a small group is speaking to an animated character.

We address the problem of identifying when a child playing an interactive game in a small group is speaking to an animated or robotic character versus conferring with his friend.

We present a hybrid stochastic/deterministic optimization scheme that uses RJMCMC to perform stochastic search over the space of detection configurations, interleaved with deterministic computation of the optimal multi-frame data association for each proposed detection hypothesis.

In this paper, we present a method which can accurately determine the identity of a team from spatiotemporal player tracking data. We do this by utilizing a formation descriptor which is found by minimizing the entropy of role-specific occupancy maps.

In this paper, we propose an “augmented- Hidden Conditional Random Field” (a-HCRF) which incorporates the local observation within the HCRF which boosts its forecasting performance.

We propose a method of representing audience behavior through facial and body motions from a single video stream and use these motions to predict the rating for feature-length movies.

We propose a weakly-supervised framework for object detection where we discover subcategories and the composites automatically with only traditional object-level category labels as input.

In this paper, we consider optimization as an approach for quickly and flexibly developing hybrid cognitive capabilities that are efficient, scalable, and can exploit knowledge to improve solution speed and quality.

We describe how the powerful “Divide and Concur” algorithm for constraint satisfaction can be derived as a special case of a message-passing version of the Alternating Direction Method of Multipliers (ADMM) algorithm for convex optimization, and introduce an improved message-passing algorithm based on ADMM/DC by introducing three distinct weights for messages, with “certain” and “no opinion” weights, as well as the standard weight used in ADMM/DC.