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09/17/2023
Active Learning for Semantic Segmentation with Multi-class Label Query
This paper proposes a new active learning method for semantic segmentati...
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09/11/2023
Addressing Feature Imbalance in Sound Source Separation
Neural networks often suffer from a feature preference problem, where th...
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03/29/2023
Adaptive Superpixel for Active Learning in Semantic Segmentation
Learning semantic segmentation requires pixel-wise annotations, which ca...
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08/13/2022
Combating Label Distribution Shift for Active Domain Adaptation
We consider the problem of active domain adaptation (ADA) to unlabeled t...
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08/11/2022
Towards Sequence-Level Training for Visual Tracking
Despite the extensive adoption of machine learning on the task of visual...
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06/01/2022
Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning
In deep reinforcement learning (RL), data augmentation is widely conside...
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05/31/2022
Few-Shot Unlearning by Model Inversion
We consider the problem of machine unlearning to erase a target dataset,...
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05/30/2022
MetaSSD: Meta-Learned Self-Supervised Detection
Deep learning-based symbol detector gains increasing attention due to th...
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11/01/2021
Robust Deep Learning from Crowds with Belief Propagation
Crowdsourcing systems enable us to collect noisy labels from crowd worke...
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10/30/2021
Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution
Audio super resolution aims to predict the missing high resolution compo...
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10/28/2021
Gradient Inversion with Generative Image Prior
Federated Learning (FL) is a distributed learning framework, in which th...
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10/23/2021
Multi-armed Bandit Algorithm against Strategic Replication
We consider a multi-armed bandit problem in which a set of arms is regis...
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02/17/2021
Time Matters in Using Data Augmentation for Vision-based Deep Reinforcement Learning
Data augmentation technique from computer vision has been widely conside...
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02/04/2021
Transfer Learning in Bandits with Latent Continuity
Structured stochastic multi-armed bandits provide accelerated regret rat...
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10/14/2019
Optimal Clustering from Noisy Binary Feedback
We study the problem of recovering clusters from binary user feedback. I...
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06/03/2018
Exploration in Structured Reinforcement Learning
We address reinforcement learning problems with finite state and action ...
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05/04/2018
Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications (Extended Version)
We study the Combinatorial Pure Exploration problem with Continuous and ...
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04/09/2018
On the Posted Pricing in Crowdsourcing: Power of Bonus
In practical crowdsourcing systems such as Amazon Mechanical Turk, poste...
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02/28/2017
Iterative Bayesian Learning for Crowdsourced Regression
Crowdsourcing platforms emerged as popular venues for purchasing human i...
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02/11/2016