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2020 – today
- 2024
[j2]Xuxing Chen, Tesi Xiao, Krishnakumar Balasubramanian:
Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions. J. Mach. Learn. Res. 25: 151:1-151:51 (2024)- [c7]Yinuo Ren, Tesi Xiao, Tanmay Gangwani, Anshuka Rangi, Holakou Rahmanian, Lexing Ying, Subhajit Sanyal:
Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow. AISTATS 2024: 3862-3870 - [c6]Xun Tang, Michael Shavlovsky, Holakou Rahmanian, Elisa Tardini, Kiran Koshy Thekumparampil, Tesi Xiao, Lexing Ying:
Accelerating Sinkhorn algorithm with sparse Newton iterations. ICLR 2024 - [i11]Xun Tang, Michael Shavlovsky, Holakou Rahmanian, Elisa Tardini, Kiran Koshy Thekumparampil, Tesi Xiao, Lexing Ying:
Accelerating Sinkhorn Algorithm with Sparse Newton Iterations. CoRR abs/2401.12253 (2024) - [i10]Xun Tang, Holakou Rahmanian, Michael Shavlovsky, Kiran Koshy Thekumparampil, Tesi Xiao, Lexing Ying:
A Sinkhorn-type Algorithm for Constrained Optimal Transport. CoRR abs/2403.05054 (2024) - [i9]Yinuo Ren, Tesi Xiao, Michael Shavlovsky, Lexing Ying, Holakou Rahmanian:
HyperDPO: Hypernetwork-based Multi-Objective Fine-Tuning Framework. CoRR abs/2410.08316 (2024) - [i8]Chenyang Yang, Tesi Xiao, Michael Shavlovsky, Christian Kästner, Tongshuang Wu:
Orbit: A Framework for Designing and Evaluating Multi-objective Rankers. CoRR abs/2411.04798 (2024) - 2023
- [c5]Tesi Xiao
, Branislav Kveton, Sumeet Katariya, Tanmay Gangwani, Anshuka Rangi:
Towards Sequential Counterfactual Learning to Rank. SIGIR-AP 2023: 122-128 - [c4]Tesi Xiao, Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi:
A one-sample decentralized proximal algorithm for non-convex stochastic composite optimization. UAI 2023: 2324-2334 - [i7]Tesi Xiao, Xuxing Chen, Krishnakumar Balasubramanian, Saeed Ghadimi:
A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization. CoRR abs/2302.09766 (2023) - [i6]Xuxing Chen, Tesi Xiao, Krishnakumar Balasubramanian:
Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions. CoRR abs/2306.12067 (2023) - [i5]Yinuo Ren, Tesi Xiao, Tanmay Gangwani, Anshuka Rangi, Holakou Rahmanian, Lexing Ying, Subhajit Sanyal:
Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow. CoRR abs/2311.13159 (2023) - 2022
- [j1]Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi:
Improved complexities for stochastic conditional gradient methods under interpolation-like conditions. Oper. Res. Lett. 50(2): 184-189 (2022) - [c3]Tesi Xiao, Xia Xiao, Ming Chen, Youlong Chen:
Field-wise Embedding Size Search via Structural Hard Auxiliary Mask Pruning for Click-Through Rate Prediction. DL4SR@CIKM 2022 - [c2]Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi:
A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization. NeurIPS 2022 - [i4]Tesi Xiao, Xia Xiao, Ming Chen, Youlong Chen:
Field-wise Embedding Size Search via Structural Hard Auxiliary Mask Pruning for Click-Through Rate Prediction. CoRR abs/2208.08004 (2022) - 2021
- [i3]Yanhao Jin, Tesi Xiao, Krishnakumar Balasubramanian:
Statistical Inference for Polyak-Ruppert Averaged Zeroth-order Stochastic Gradient Algorithm. CoRR abs/2102.05198 (2021) - 2020
- [c1]Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh:
How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework. CVPR 2020: 279-287 - [i2]Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi:
Improved Complexities for Stochastic Conditional Gradient Methods under Interpolation-like Conditions. CoRR abs/2006.08167 (2020)
2010 – 2019
- 2019
- [i1]Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh:
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise. CoRR abs/1906.02355 (2019)
Coauthor Index
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