1.5k citations · 2.2k across the 25 of their papers we have counts for
6 papers · 1 filter
Kernelized Hashcode Representations for Relation Extraction
Sahil Garg, Aram Galstyan, Greg Ver Steeg +3
Kernel methods have produced state-of-the-art results for a number of NLP tasks such as relation extraction, but suffer from poor scalability due to the high cost of computing kern…
Efficient Data Representation by Selecting Prototypes with Importance Weights
Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo Cecchi +1
Prototypical examples that best summarizes and compactly represents an underlying complex data distribution communicate meaningful insights to humans in domains where simple explan…
Bandit Models of Human Behavior: Reward Processing in Mental Disorders
Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi
Drawing an inspiration from behavioral studies of human decision making, we propose here a general parametric framework for multi-armed bandit problem, which extends the standard T…
Context Attentive Bandits: Contextual Bandit with Restricted Context
Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi +1
We consider a novel formulation of the multi-armed bandit model, which we call the contextual bandit with restricted context, where only a limited number of features can be accesse…
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World
Sahil Garg, Irina Rish, Guillermo Cecchi +1
In this paper, we focus on online representation learning in non-stationary environments which may require continuous adaptation of model architecture. We propose a novel online di…
NIPS 2016 Workshop on Representation Learning in Artificial and Biological Neural Networks (MLINI 2016)
Leila Wehbe, Anwar Nunez-Elizalde, Marcel van Gerven +5
This workshop explores the interface between cognitive neuroscience and recent advances in AI fields that aim to reproduce human performance such as natural language processing and…