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01/28/2023
Zero-shot causal learning
Predicting how different interventions will causally affect a specific i...
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10/20/2022
Estimating fine age structure and time trends in human contact patterns from coarse contact data: the Bayesian rate consistency model
Since the emergence of severe acute respiratory syndrome coronavirus 2 (...
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08/23/2022
Entropy Enhanced Multi-Agent Coordination Based on Hierarchical Graph Learning for Continuous Action Space
In most existing studies on large-scale multi-agent coordination, the co...
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04/12/2022
Stylized Knowledge-Grounded Dialogue Generation via Disentangled Template Rewriting
Current Knowledge-Grounded Dialogue Generation (KDG) models specialize i...
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09/25/2021
Learning Neural Templates for Recommender Dialogue System
Though recent end-to-end neural models have shown promising progress on ...
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07/28/2021
Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers
A common lens to theoretically study neural net architectures is to anal...
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07/15/2021
Nonparametric, tuning-free estimation of S-shaped functions
We consider the nonparametric estimation of an S-shaped regression funct...
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06/18/2021
Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments
Domain generalization aims at performing well on unseen test environment...
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05/27/2021
Maria: A Visual Experience Powered Conversational Agent
Arguably, the visual perception of conversational agents to the physical...
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10/07/2020
Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data
Self-training algorithms, which train a model to fit pseudolabels predic...
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06/29/2020
Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization
Real-world large-scale datasets are heteroskedastic and imbalanced – lab...
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06/25/2020
Active Online Domain Adaptation
Online machine learning systems need to adapt to domain shifts. Meanwhil...
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06/17/2020
Self-training Avoids Using Spurious Features Under Domain Shift
In unsupervised domain adaptation, existing theory focuses on situations...
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05/19/2020
Experience Augmentation: Boosting and Accelerating Off-Policy Multi-Agent Reinforcement Learning
Exploration of the high-dimensional state action space is one of the big...
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01/28/2020
A random forest based approach for predicting spreads in the primary catastrophe bond market
We introduce a random forest approach to enable spreads' prediction in t...
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10/22/2019
Weakly Supervised Disentanglement with Guarantees
Learning disentangled representations that correspond to factors of vari...
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06/19/2019
An axiomatic nonparametric production function estimator: Modeling production in Japan's cardboard industry
We develop a new approach to estimate a production function based on the...
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09/12/2018
Retrieval-Enhanced Adversarial Training for Neural Response Generation
Dialogue systems are usually built on either generation-based or retriev...
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12/04/2017
Time-Space Tradeoffs for the Memory Game
A single-player Memory Game is played with n distinct pairs of cards, wi...
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11/15/2017