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07/07/2023
Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning
Discovering achievements with a hierarchical structure on procedurally g...
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05/27/2023
Query-Efficient Black-Box Red Teaming via Bayesian Optimization
The deployment of large-scale generative models is often restricted by t...
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01/30/2023
Designing an offline reinforcement learning objective from scratch
Offline reinforcement learning has developed rapidly over the recent yea...
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01/29/2023
Neural Relation Graph for Identifying Problematic Data
Diagnosing and cleaning datasets are crucial for building robust machine...
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01/28/2023
Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming
Recent works on neural network pruning advocate that reducing the depth ...
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10/18/2022
Rethinking Value Function Learning for Generalization in Reinforcement Learning
We focus on the problem of training RL agents on multiple training envir...
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06/17/2022
Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization
We focus on the problem of adversarial attacks against models on discret...
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05/30/2022
Dataset Condensation via Efficient Synthetic-Data Parameterization
The great success of machine learning with massive amounts of data comes...
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02/24/2022
Optimal channel selection with discrete QCQP
Reducing the high computational cost of large convolutional neural netwo...
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12/10/2021
Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks
Deep neural networks have become the driving force of modern image recog...
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10/04/2021
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
Offline reinforcement learning (offline RL), which aims to find an optim...
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02/05/2021
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
While deep neural networks show great performance on fitting to the trai...
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09/15/2020
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup
While deep neural networks achieve great performance on fitting the trai...
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05/23/2019
Learning Discrete and Continuous Factors of Data via Alternating Disentanglement
We address the problem of unsupervised disentanglement of discrete and c...
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05/16/2019
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization
Solving for adversarial examples with projected gradient descent has bee...
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02/28/2019
End-to-End Efficient Representation Learning via Cascading Combinatorial Optimization
We develop hierarchically quantized efficient embedding representations ...
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10/02/2018
EMI: Exploration with Mutual Information Maximizing State and Action Embeddings
Policy optimization struggles when the reward feedback signal is very sp...
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05/15/2018
Efficient end-to-end learning for quantizable representations
Embedding representation learning via neural networks is at the core fou...
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03/30/2017
Semantic Instance Segmentation via Deep Metric Learning
We propose a new method for semantic instance segmentation, by first com...
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12/05/2016
Deep Metric Learning via Facility Location
Learning the representation and the similarity metric in an end-to-end f...
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02/10/2016
Unsupervised Transductive Domain Adaptation
Supervised learning with large scale labeled datasets and deep layered m...
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06/25/2014
Weakly-supervised Discovery of Visual Pattern Configurations
The increasing prominence of weakly labeled data nurtures a growing dema...
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05/28/2014
