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Journal Articles
- 2019
[j1]Bin Niu, Jiawei Kong, Shaofei Tang, Yingcong Li, Zuqing Zhu
:
Visualize Your IP-Over-Optical Network in Realtime: A P4-Based Flexible Multilayer In-Band Network Telemetry (ML-INT) System. IEEE Access 7: 82413-82423 (2019)
Conference and Workshop Papers
- 2024
- [c10]Yingcong Li, Yixiao Huang, Muhammed Emrullah Ildiz, Ankit Singh Rawat, Samet Oymak:
Mechanics of Next Token Prediction with Self-Attention. AISTATS 2024: 685-693 - [c9]Muhammed Emrullah Ildiz, Yixiao Huang, Yingcong Li, Ankit Singh Rawat, Samet Oymak:
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers. ICML 2024 - 2023
- [c8]Yingcong Li, Samet Oymak:
Provable Pathways: Learning Multiple Tasks over Multiple Paths. AAAI 2023: 8701-8710 - [c7]Yuzhen Qin, Yingcong Li, Fabio Pasqualetti, Maryam Fazel, Samet Oymak:
Stochastic Contextual Bandits with Long Horizon Rewards. AAAI 2023: 9525-9533 - [c6]Yingcong Li, Samet Oymak:
On The Fairness of Multitask Representation Learning. ICASSP 2023: 1-5 - [c5]Yingcong Li, Muhammed Emrullah Ildiz, Dimitris Papailiopoulos, Samet Oymak:
Transformers as Algorithms: Generalization and Stability in In-context Learning. ICML 2023: 19565-19594 - [c4]Yingcong Li, Kartik Sreenivasan, Angeliki Giannou, Dimitris Papailiopoulos, Samet Oymak:
Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning. NeurIPS 2023 - [c3]Davoud Ataee Tarzanagh, Yingcong Li, Xuechen Zhang, Samet Oymak:
Max-Margin Token Selection in Attention Mechanism. NeurIPS 2023 - 2021
- [c2]Xiangyu Chang, Yingcong Li, Samet Oymak, Christos Thrampoulidis:
Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks. AAAI 2021: 6974-6983 - 2019
- [c1]Zuqing Zhu, Bin Niu, Jiawei Kong, Shaofei Tang, Yingcong Li, Hongqiang Fang, Wei Lu:
Leveraging Multilayer Telemetry to Realize AI-assisted Service Provisioning in IP over Elastic Optical Networks: (Invited Paper). OECC/PSC 2019: 1-3
Informal and Other Publications
- 2024
- [i12]Muhammed Emrullah Ildiz, Yixiao Huang, Yingcong Li, Ankit Singh Rawat, Samet Oymak:
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers. CoRR abs/2402.13512 (2024) - [i11]Yingcong Li, Yixiao Huang, Muhammed Emrullah Ildiz, Ankit Singh Rawat, Samet Oymak:
Mechanics of Next Token Prediction with Self-Attention. CoRR abs/2403.08081 (2024) - [i10]Yingcong Li, Ankit Singh Rawat, Samet Oymak:
Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond. CoRR abs/2407.10005 (2024) - 2023
- [i9]Yingcong Li, Muhammed Emrullah Ildiz, Dimitris S. Papailiopoulos, Samet Oymak:
Transformers as Algorithms: Generalization and Implicit Model Selection in In-context Learning. CoRR abs/2301.07067 (2023) - [i8]Yuzhen Qin, Yingcong Li, Fabio Pasqualetti, Maryam Fazel, Samet Oymak:
Stochastic Contextual Bandits with Long Horizon Rewards. CoRR abs/2302.00814 (2023) - [i7]Yingcong Li, Samet Oymak:
Provable Pathways: Learning Multiple Tasks over Multiple Paths. CoRR abs/2303.04338 (2023) - [i6]Yingcong Li, Kartik Sreenivasan, Angeliki Giannou, Dimitris S. Papailiopoulos, Samet Oymak:
Dissecting Chain-of-Thought: A Study on Compositional In-Context Learning of MLPs. CoRR abs/2305.18869 (2023) - [i5]Davoud Ataee Tarzanagh, Yingcong Li, Xuechen Zhang, Samet Oymak:
Max-Margin Token Selection in Attention Mechanism. CoRR abs/2306.13596 (2023) - [i4]Davoud Ataee Tarzanagh, Yingcong Li, Christos Thrampoulidis, Samet Oymak:
Transformers as Support Vector Machines. CoRR abs/2308.16898 (2023) - 2022
- [i3]Yingcong Li, Mingchen Li, M. Salman Asif, Samet Oymak:
Provable and Efficient Continual Representation Learning. CoRR abs/2203.02026 (2022) - [i2]Yingcong Li, Chandra Sekhar Mukherjee, Jiapeng Zhang:
Confident Clustering via PCA Compression Ratio and Its Application to Single-cell RNA-seq Analysis. CoRR abs/2205.09849 (2022) - 2020
- [i1]Xiangyu Chang, Yingcong Li, Samet Oymak, Christos Thrampoulidis:
Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks. CoRR abs/2012.08749 (2020)
Coauthor Index
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