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08/01/2023
Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs
Finding a high-quality feasible solution to a combinatorial optimization...
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02/13/2023
Bag of Tricks for In-Distribution Calibration of Pretrained Transformers
While pre-trained language models (PLMs) have become a de-facto standard...
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12/22/2021
A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drone
Reinforcement learning has recently shown promise in learning quality so...
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10/24/2020
Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards
In this paper, we consider stochastic multi-armed bandits (MABs) with he...
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10/02/2020
Neural Bootstrapper
Bootstrapping has been a primary tool for uncertainty quantification, an...
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05/09/2020
AutoCLINT: The Winning Method in AutoCV Challenge 2019
NeurIPS 2019 AutoDL challenge is a series of six automated machine learn...
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04/21/2020
torchgpipe: On-the-fly Pipeline Parallelism for Training Giant Models
We design and implement a ready-to-use library in PyTorch for performing...
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06/13/2019
Scalable Neural Architecture Search for 3D Medical Image Segmentation
In this paper, a neural architecture search (NAS) framework is proposed ...
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05/01/2019
Fast AutoAugment
Data augmentation is an indispensable technique to improve generalizatio...
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01/31/2019
Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning
In this paper, we present a new class of Markov decision processes (MDPs...
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05/16/2018
ChoiceNet: Robust Learning by Revealing Output Correlations
In this paper, we focus on the supervised learning problem with corrupte...
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10/23/2017
Neural Stain-Style Transfer Learning using GAN for Histopathological Images
Performance of data-driven network for tumor classification varies with ...
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09/03/2017
