A universal data model, named DG, is introduced to handle vectorized data uniformly during the whole recognition process. The model supports low level graph algorithms as well as h...
This paper presents a graphical model for learning and recognizing human actions. Specifically, we propose to encode actions in a weighted directed graph, referred to as action gra...
This paper deals with chain graph models under alternative AMP interpretation. A new representative of an AMP Markov equivalence class, called the largest deflagged graph, is prop...
Abstract. With the adoption of tablet-based data entry devices, there is considerable interest in methods for converting hand-drawn sketches of flow charts, graphs and block diagr...
Akshaya Kumar Mishra, Justin A. Eichel, Paul W. Fi...
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...