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Poster
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Fri 16:30
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Non-geodesically-convex optimization in the Wasserstein space
Hoang Phuc Hau Luu · Hanlin Yu · Bernardo Williams · Petrus Mikkola · Marcelo Hartmann · Kai Puolamäki · Arto Klami
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Poster
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Fri 11:00
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Quantum Algorithms for Non-smooth Non-convex Optimization
Chengchang Liu · Chaowen Guan · Jianhao He · John C. S. Lui
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Poster
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Thu 11:00
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On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions
Yusu Hong · Junhong Lin
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Poster
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Thu 16:30
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Optimization Can Learn Johnson Lindenstrauss Embeddings
Nikos Tsikouras · Constantine Caramanis · Christos Tzamos
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Poster
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Thu 11:00
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Ordered Momentum for Asynchronous SGD
Chang-Wei Shi · Yi-Rui Yang · Wu-Jun Li
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Poster
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Fri 16:30
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Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions
Wei Jiang · Sifan Yang · Yibo Wang · Lijun Zhang
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Poster
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Wed 16:30
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Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction
Wei Jiang · Sifan Yang · Wenhao Yang · Lijun Zhang
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Workshop
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Intuitive Analysis of the Quantization based Optimization : From establishing a SDE to Quantum Mechanical Perspective
Jinwuk Seok · Changsik Cho
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Workshop
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Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
Binghui Li · Yuanzhi Li
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Poster
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Thu 11:00
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Quantitative Convergences of Lie Group Momentum Optimizers
Lingkai Kong · Molei Tao
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Poster
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Wed 16:30
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A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization
Yizun Lin · Zhao-Rong Lai · Cheng Li
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Poster
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Learnability of high-dimensional targets by two-parameter models and gradient flow
Dmitry Yarotsky
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