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08/11/2023
DF2: Distribution-Free Decision-Focused Learning
Decision-focused learning (DFL) has recently emerged as a powerful appro...
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07/17/2023
Autoregressive Diffusion Model for Graph Generation
Diffusion-based graph generative models have recently obtained promising...
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05/30/2023
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling
Learning from noisy labels is a challenge that arises in many real-world...
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05/26/2023
AdaPlanner: Adaptive Planning from Feedback with Language Models
Large language models (LLMs) have recently demonstrated the potential in...
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11/25/2022
End-to-End Stochastic Optimization with Energy-Based Model
Decision-focused learning (DFL) was recently proposed for stochastic opt...
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05/27/2022
Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport
The problem of optimization on Stiefel manifold, i.e., minimizing functi...
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12/16/2021
ATM: An Uncertainty-aware Active Self-training Framework for Label-efficient Text Classification
Despite the great success of pre-trained language models (LMs) in many n...
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06/07/2021
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
Accurate and trustworthy epidemic forecasting is an important problem th...
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10/22/2020
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
Fine-tuned pre-trained language models can suffer from severe miscalibra...
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08/24/2020
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
Uncertainty quantification is a fundamental yet unsolved problem for dee...
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02/14/2020
Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function
This article suggests that deterministic Gradient Descent, which does no...
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07/22/2018