We are pleased to announce the ARC-ACO fellowship winners for Spring 2023:
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Guanghui Wang (ML CS) |
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Adaptive and Oracle-Efficient Online Learning |
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Tian-Yi Zhou (ISyE OR) |
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Classification of Unbounded Data by Gaussian Mixture Models Using deep ReLU Networks |
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Jai Moondra (ACO CS) |
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Fair and interpretable combinatorial optimization using symmetric weights |
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Yumbum Kook (CS) |
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Further Development of High-dimensional Sampling |
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Yuzhou Wang (ACO Math) |
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Hardness of finding balanced independent sets in d-regular random bipartite graphs |
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Yongchun Li (OR ISyE) |
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On the Strength of Dantzig-Wolfe Relaxation of Rank Constrained Optimization: Exactness, Rank Bound, and Algorithm |
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Sajad Khodadadian (OR ISyE) |
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Sharp Analysis of Two-Time-Scale Stochastic Approximation with Applications in Reinforcement Learning |
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Kevin Shu (ACO Math) |
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Sparsity and Randomness in Optimization |
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Xinyuan Cao (ML CS) |
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Unsupervised Learning of Halfspaces and Beyond |
Congratulations to all of them. We received 23 applications including many excellent proposals that we could not accept. Many thanks to the selection committee of Jan van den Brand, Debankur Mukherjee, Will Perkins, Mohit Singh, Santosh Vempala and Josephine Yu.
