research
∙
02/20/2020
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision
We consider the post-training quantization problem, which discretizes th...
share
research
∙
10/16/2019
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation
Infinite horizon off-policy policy evaluation is a highly challenging ta...
research
∙
11/06/2018
Neural Phrase-to-Phrase Machine Translation
In this paper, we propose Neural Phrase-to-Phrase Machine Translation (N...
research
∙
10/29/2018
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation
We consider the off-policy estimation problem of estimating the expected...
research
∙
11/07/2017
On the Discrimination-Generalization Tradeoff in GANs
Generative adversarial training can be generally understood as minimizin...
research
∙
10/30/2017
Sample-efficient Policy Optimization with Stein Control Variate
Policy gradient methods have achieved remarkable successes in solving ch...
research
∙
06/17/2017
Towards Neural Phrase-based Machine Translation
In this paper, we present Neural Phrase-based Machine Translation (NPMT)...
research
∙
02/28/2017
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Contextual bandits are widely used in Internet services from news recomm...
research
∙
02/25/2017
Stochastic Variance Reduction Methods for Policy Evaluation
Policy evaluation is a crucial step in many reinforcement-learning proce...
research
∙
02/24/2017
Sequence Modeling via Segmentations
Segmental structure is a common pattern in many types of sequences such ...
research
∙
11/06/2016
Neuro-Symbolic Program Synthesis
Recent years have seen the proposal of a number of neural architectures ...
research
∙
05/25/2016
Exact Exponent in Optimal Rates for Crowdsourcing
In many machine learning applications, crowdsourcing has become the prim...
research
∙
03/25/2015
Regularized Minimax Conditional Entropy for Crowdsourcing
There is a rapidly increasing interest in crowdsourcing for data labelin...
research
∙
02/19/2015
Approval Voting and Incentives in Crowdsourcing
The growing need for labeled training data has made crowdsourcing an imp...
research
∙
11/21/2014
On the Impossibility of Convex Inference in Human Computation
Human computation or crowdsourcing involves joint inference of the groun...
research
∙
03/12/2014
Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling
In crowd labeling, a large amount of unlabeled data instances are outsou...
research
∙
07/10/2013
