Context Sensitive Modeling of Cancer Drug Sensitivity

Context Sensitive Modeling of Cancer Drug Sensitivity

Recent screening of drug sensitivity in large panels of cancer cell lines provides a valuable resource towards developing algorithms that predict drug response. Since more samples provide increased statistical power, most approaches to prediction of drug sensitivity pool multiple cancer types together without distinction. However, pan-cancer results can be misleading due to the confounding effe...

Towards Context-sensitive Modeling Tools

Context-sensitive statistical language modeling

We present context-sensitive dynamic classes – a novel mechanism for integrating contextual information from spoken dialogue into a class n-gram language model. We exploit the dialogue system’s information state to populate dynamic classes, thus percolating contextual constraints to the recognizer’s language model in real time. We describe a technique for training a language model incorporating...

COSMOS: A Context-Sensitive Probabilistic Modeling System

OF DISSERTATION Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Computer Science The University of New Mexico Albuquerque, New Mexico

Cognitive Modeling with Context Sensitive Reinforcement Learning

A reinforcement learning system is typically described as a black box which receives two types of input, the current state, S, and the current reinforcement, R. From these two inputs, the system has to figure out a policy that determines what action to perform in each state to maximize the received reinforcement in the future (Sutton & Barto, 1998). The future expected reinforcement can be esti...