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07/06/2023
Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment
Human communication often involves information gaps between the interloc...
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05/31/2023
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
Despite the seeming success of contemporary grounded text generation sys...
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07/25/2022
Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning
Despite recent advances in natural language understanding and generation...
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04/10/2022
Active Learning with Label Comparisons
Supervised learning typically relies on manual annotation of the true la...
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11/04/2021
Flood forecasting with machine learning models in an operational framework
The operational flood forecasting system by Google was developed to prov...
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05/05/2021
Solving Sokoban with backward reinforcement learning
In some puzzles, the strategy we need to use near the goal can be quite ...
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04/27/2021
Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Image classification models can depend on multiple different semantic at...
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11/29/2020
ML-based Flood Forecasting: Advances in Scale, Accuracy and Reach
Floods are among the most common and deadly natural disasters in the wor...
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07/01/2020
HydroNets: Leveraging River Structure for Hydrologic Modeling
Accurate and scalable hydrologic models are essential building blocks of...
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06/11/2020
DNF-Net: A Neural Architecture for Tabular Data
A challenging open question in deep learning is how to handle tabular da...
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04/21/2020
Normalizing Flow Regression
In this letter we propose a convex approach to learning expressive scala...
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11/03/2019
Improved Detection of Adversarial Attacks via Penetration Distortion Maximization
This paper is concerned with the defense of deep models against adversar...
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10/27/2019
Spectral Algorithm for Low-rank Multitask Regression
Multitask learning, i.e. taking advantage of the relatedness of individu...
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01/28/2019
ML for Flood Forecasting at Scale
Effective riverine flood forecasting at scale is hindered by a multitude...
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01/03/2019
Towards Global Remote Discharge Estimation: Using the Few to Estimate The Many
Learning hydrologic models for accurate riverine flood prediction at sca...
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03/08/2018
Learning with Rules
Complex classifiers may exhibit "embarassing" failures in cases that wou...
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08/16/2016
Scalable Learning of Non-Decomposable Objectives
Modern retrieval systems are often driven by an underlying machine learn...
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09/26/2013
Learning Max-Margin Tree Predictors
Structured prediction is a powerful framework for coping with joint pred...
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01/10/2013
Learning the Dimensionality of Hidden Variables
A serious problem in learning probabilistic models is the presence of hi...
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10/19/2012
The Information Bottleneck EM Algorithm
Learning with hidden variables is a central challenge in probabilistic g...
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07/11/2012
"Ideal Parent" Structure Learning for Continuous Variable Networks
In recent years, there is a growing interest in learning Bayesian networ...
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03/15/2012