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96 Results
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Affinity Event
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Markov Chain Variance Estimation: A Stochastic Approximation Approach Shubhada Agrawal · Prashanth L.A. · Siva Theja Maguluri |
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Poster
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Wed 11:00 |
No-Regret M♮-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting Taihei Oki · Shinsaku Sakaue |
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Poster
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Thu 16:30 |
Certified Machine Unlearning via Noisy Stochastic Gradient Descent Eli Chien · Haoyu Wang · Ziang Chen · Pan Li |
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Poster
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Thu 16:30 |
Stochastic Newton Proximal Extragradient Method Ruichen Jiang · Michal Derezinski · Aryan Mokhtari |
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Poster
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Wed 11:00 |
The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms Elizabeth Collins-Woodfin · Inbar Seroussi · Begoña García Malaxechebarría · Andrew W. Mackenzie · Elliot Paquette · Courtney Paquette |
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Poster
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Fri 16:30 |
A Continuous-time Stochastic Gradient Descent Method for Continuous Data Kexin Jin · Jonas Latz · Chenguang Liu · Carola-Bibiane Schönlieb |
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Poster
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Fri 16:30 |
Stochastic Optimal Control and Estimation with Multiplicative and Internal Noise Francesco Damiani · Akiyuki Anzai · Jan Drugowitsch · Gregory DeAngelis · Ruben Moreno Bote |
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Poster
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Thu 11:00 |
S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization Licheng Zhu · Mathias Oster · Yuehaw Khoo |
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Poster
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Fri 16:30 |
Stochastic Concept Bottleneck Models Moritz Vandenhirtz · Sonia Laguna · Ričards Marcinkevičs · Julia Vogt |
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Poster
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Thu 11:00 |
On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models Aditya Bhaskara · Agastya Jha · Michael Kapralov · Naren Manoj · Davide Mazzali · Weronika Wrzos-Kaminska |
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Poster
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Wed 11:00 |
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions Hilal Asi · Daogao Liu · Kevin Tian |
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Poster
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Thu 16:30 |
Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement Jeremiah Birrell · Reza Ebrahimi · Rouzbeh Behnia · Jason Pacheco |