Research
I am interested in machine learning theory, mathematical optimization, dynamical systems, and scientific computing. I am currently working in online learning and large-scale optimization with logarithmic
loss.
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Learning and optimization with logarithmic loss
Computing Augustin information via hybrid geodesically convex
optimization
Guan-Ren Wang,
Chung-En Tsai,
Hao-Chung Cheng, and
Yen-Huan Li
NOPTA 2024; ISIT 2024
arXiv
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NOPTA poster
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Fast minimization of expected logarithmic loss via stochastic
dual averaging
Chung-En Tsai,
Hao-Chung Cheng, and
Yen-Huan Li
QIP 2024; AISTATS 2024
AISTATS proceedings
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arXiv
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QIP poster
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AISTATS poster
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Data-dependent bounds for online portfolio selection without
Lipschitzness and smoothness
Chung-En Tsai,
Ying-Ting Lin, and
Yen-Huan Li
NeurIPS 2023; NOPTA 2024
NeurIPS proceedings
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arXiv
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short
intro
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NeurIPS poster
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NOPTA poster
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Faster stochastic first-order method for maximum-likelihood
quantum state tomography
Chung-En Tsai,
Hao-Chung Cheng, and
Yen-Huan Li
QIP 2023
arXiv
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Online self-concordant and relatively smooth minimization, with
applications to online portfolio selection and learning quantum states
Chung-En Tsai,
Hao-Chung Cheng, and
Yen-Huan Li
ALT 2023
ALT proceedings
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arXiv
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ALT talk
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Synchronization theory
On the synchronization analysis of a strong competition Kuramoto
model
Chun-Hsiung Hsia and
Chung-En Tsai
TMS 2023
arXiv
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TMS poster
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