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Poster
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Tue 9:00 |
Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss Jason Altschuler · Kunal Talwar |
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Poster
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Thu 14:00 |
On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity Vincent Szolnoky · Viktor Andersson · Balazs Kulcsar · Rebecka Jörnsten |
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Poster
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Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning Shikun Li · Xiaobo Xia · Hansong Zhang · Yibing Zhan · Shiming Ge · Tongliang Liu |
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Poster
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Confidence-based Reliable Learning under Dual Noises Peng Cui · Yang Yue · Zhijie Deng · Jun Zhu |
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Poster
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Thu 14:00 |
Is one annotation enough? - A data-centric image classification benchmark for noisy and ambiguous label estimation Lars Schmarje · Vasco Grossmann · Claudius Zelenka · Sabine Dippel · Rainer Kiko · Mariusz Oszust · Matti Pastell · Jenny Stracke · Anna Valros · Nina Volkmann · Reinhard Koch |
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Poster
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Tue 9:00 |
Active Ranking without Strong Stochastic Transitivity Hao Lou · Tao Jin · Yue Wu · Pan Xu · Quanquan Gu · Farzad Farnoud |
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Poster
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Self-Supervised Image Restoration with Blurry and Noisy Pairs Zhilu Zhang · RongJian Xu · Ming Liu · Zifei Yan · Wangmeng Zuo |
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Poster
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SoftPatch: Unsupervised Anomaly Detection with Noisy Data Xi Jiang · Jianlin Liu · Jinbao Wang · Qiang Nie · Kai WU · Yong Liu · Chengjie Wang · Feng Zheng |
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Poster
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MVP-N: A Dataset and Benchmark for Real-World Multi-View Object Classification REN WANG · Jiayue Wang · Tae Sung Kim · JINSUNG KIM · Hyuk-Jae Lee |
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Poster
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Thu 14:00 |
Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data Yusuke Tanaka · Tomoharu Iwata · naonori ueda |
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Poster
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Tue 9:00 |
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence) Jiayuan Ye · Reza Shokri |
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Panel
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Tue 10:00 |
Panel 1C-5: Privacy of Noisy… & Near-Optimal Private and… Shyam Narayanan · Kunal Talwar |