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An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning


Nov 20, 2022
Hao Chen, Yue Fan, Yidong Wang, Jindong Wang, Bernt Schiele, Xing Xie, Marios Savvides, Bhiksha Raj

* Imbalanced Semi-Supervised Learning 

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Describing emotions with acoustic property prompts for speech emotion recognition


Nov 14, 2022
Hira Dhamyal, Benjamin Elizalde, Soham Deshmukh, Huaming Wang, Bhiksha Raj, Rita Singh


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XNOR-FORMER: Learning Accurate Approximations in Long Speech Transformers


Oct 29, 2022
Roshan Sharma, Bhiksha Raj

* Under review at ICASSP 2023 

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Unifying the Discrete and Continuous Emotion labels for Speech Emotion Recognition


Oct 29, 2022
Roshan Sharma, Hira Dhamyal, Bhiksha Raj, Rita Singh

* Under Review at ICASSP 2023 

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There is more than one kind of robustness: Fooling Whisper with adversarial examples


Oct 26, 2022
Raphael Olivier, Bhiksha Raj


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Privacy-preserving Automatic Speaker Diarization


Oct 26, 2022
Francisco Teixeira, Alberto Abad, Bhiksha Raj, Isabel Trancoso


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AOE-Net: Entities Interactions Modeling with Adaptive Attention Mechanism for Temporal Action Proposals Generation


Oct 05, 2022
Khoa Vo, Sang Truong, Kashu Yamazaki, Bhiksha Raj, Minh-Triet Tran, Ngan Le

* Accepted for publication in International Journal of Computer Vision 

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Watch What You Pretrain For: Targeted, Transferable Adversarial Examples on Self-Supervised Speech Recognition models


Sep 29, 2022
Raphael Olivier, Hadi Abdullah, Bhiksha Raj


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USB: A Unified Semi-supervised Learning Benchmark


Aug 12, 2022
Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yu-Feng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang

* Submitted to NeurIPS'22 dataset and benchmark track; code at https://github.com/microsoft/Semi-supervised-learning 

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Online Video Instance Segmentation via Robust Context Fusion


Jul 12, 2022
Xiang Li, Jinglu Wang, Xiaohao Xu, Bhiksha Raj, Yan Lu


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