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Journal Articles
- 2024
[j6]Arvind U. Raghunathan, David Bergman
, John N. Hooker, Thiago Serra, Shingo Kobori:
Seamless Multimodal Transportation Scheduling. INFORMS J. Comput. 36(2): 336-358 (2024)- 2022
- [j5]Thiago Serra, Teng Huang, Arvind U. Raghunathan, David Bergman:
Template-Based Minor Embedding for Adiabatic Quantum Optimization. INFORMS J. Comput. 34(1): 427-439 (2022) - 2020
- [j4]Thiago Serra:
Reformulating the disjunctive cut generating linear program. Ann. Oper. Res. 295(1): 363-384 (2020) - [j3]Egon Balas, Thiago Serra:
When Lift-and-Project Cuts Are Different. INFORMS J. Comput. 32(3): 822-834 (2020) - [j2]Thiago Serra, John N. Hooker:
Compact representation of near-optimal integer programming solutions. Math. Program. 182(1): 199-232 (2020) - [j1]Thiago Serra, Ryan J. O'Neil:
MIPLIBing: Seamless Benchmarking of Mathematical Optimization Problems and Metadata Extensions. Oper. Res. Forum 1(3) (2020)
Conference and Workshop Papers
- 2024
- [c15]Jiatai Tong, Junyang Cai, Thiago Serra:
Optimization over Trained Neural Networks: Taking a Relaxing Walk. CPAIOR (2) 2024: 221-233 - 2023
- [c14]Alexandre M. Florio, Pedro Martins, Maximilian Schiffer, Thiago Serra, Thibaut Vidal:
Optimal Decision Diagrams for Classification. AAAI 2023: 7577-7585 - [c13]Junyang Cai, Khai-Nguyen Nguyen, Nishant Shrestha, Aidan Good, Ruisen Tu, Xin Yu, Shandian Zhe, Thiago Serra:
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions. CPAIOR 2023: 200-218 - 2022
- [c12]Carles Roger Riera Molina, Camilo Rey, Thiago Serra, Eloi Puertas, Oriol Pujol:
Training Thinner and Deeper Neural Networks: Jumpstart Regularization. CPAIOR 2022: 345-357 - [c11]Xin Yu, Thiago Serra, Srikumar Ramalingam, Shandian Zhe:
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks. ICML 2022: 25668-25683 - [c10]Aidan Good, Jiaqi Lin, Xin Yu, Hannah Sieg, Mikey Ferguson, Shandian Zhe, Jerzy Wieczorek, Thiago Serra:
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm. NeurIPS 2022 - 2021
- [c9]Thiago Serra, Xin Yu, Abhinav Kumar, Srikumar Ramalingam:
Scaling Up Exact Neural Network Compression by ReLU Stability. NeurIPS 2021: 27081-27093 - 2020
- [c8]Thiago Serra, Srikumar Ramalingam:
Empirical Bounds on Linear Regions of Deep Rectifier Networks. AAAI 2020: 5628-5635 - [c7]Thiago Serra:
Enumerative Branching with Less Repetition. CPAIOR 2020: 399-416 - [c6]Thiago Serra, Abhinav Kumar, Srikumar Ramalingam:
Lossless Compression of Deep Neural Networks. CPAIOR 2020: 417-430 - [c5]Thiago Serra, Srikumar Ramalingam:
Empirical Bounds on Linear Regions of Deep Rectifier Networks. ISAIM 2020 - 2019
- [c4]Thiago Serra, Arvind U. Raghunathan, David Bergman, John N. Hooker, Shingo Kobori:
Last-Mile Scheduling Under Uncertainty. CPAIOR 2019: 519-528 - 2018
- [c3]Arvind U. Raghunathan, David Bergman, John N. Hooker, Thiago Serra, Shingo Kobori:
The Integrated Last-Mile Transportation Problem (ILMTP). ICAPS 2018: 388-398 - [c2]Thiago Serra, Christian Tjandraatmadja, Srikumar Ramalingam:
Bounding and Counting Linear Regions of Deep Neural Networks. ICML 2018: 4565-4573 - 2012
- [c1]Thiago Serra, Gilberto Nishioka, Fernando J. M. Marcellino:
The Offshore Resources Scheduling Problem: Detailing a Constraint Programming Approach. CP 2012: 823-839
Informal and Other Publications
- 2024
- [i16]Jiatai Tong, Junyang Cai, Thiago Serra:
Optimization Over Trained Neural Networks: Taking a Relaxing Walk. CoRR abs/2401.03451 (2024) - 2023
- [i15]Junyang Cai, Khai-Nguyen Nguyen, Nishant Shrestha, Aidan Good, Ruisen Tu, Xin Yu, Shandian Zhe, Thiago Serra:
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions. CoRR abs/2301.07966 (2023) - [i14]Joey Huchette, Gonzalo Muñoz, Thiago Serra, Calvin Tsay:
When Deep Learning Meets Polyhedral Theory: A Survey. CoRR abs/2305.00241 (2023) - [i13]Fabian Badilla, Marcos Goycoolea, Gonzalo Muñoz, Thiago Serra:
Computational Tradeoffs of Optimization-Based Bound Tightening in ReLU Networks. CoRR abs/2312.16699 (2023) - 2022
- [i12]Carles Roger Riera Molina, Camilo Rey, Thiago Serra, Eloi Puertas, Oriol Pujol:
Training Thinner and Deeper Neural Networks: Jumpstart Regularization. CoRR abs/2201.12795 (2022) - [i11]Xin Yu, Thiago Serra, Srikumar Ramalingam, Shandian Zhe:
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks. CoRR abs/2203.04466 (2022) - [i10]Alexandre M. Florio, Pedro Martins, Maximilian Schiffer, Thiago Serra, Thibaut Vidal:
Optimal Decision Diagrams for Classification. CoRR abs/2205.14500 (2022) - [i9]Aidan Good, Jiaqi Lin, Hannah Sieg, Mikey Ferguson, Xin Yu, Shandian Zhe, Jerzy Wieczorek, Thiago Serra:
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm. CoRR abs/2206.02976 (2022) - 2021
- [i8]Thiago Serra, Xin Yu, Abhinav Kumar, Srikumar Ramalingam:
Scaling Up Exact Neural Network Compression by ReLU Stability. CoRR abs/2102.07804 (2021) - 2020
- [i7]Thiago Serra, Abhinav Kumar, Srikumar Ramalingam:
Lossless Compression of Deep Neural Networks. CoRR abs/2001.00218 (2020) - 2019
- [i6]Abhinav Kumar, Thiago Serra, Srikumar Ramalingam:
Equivalent and Approximate Transformations of Deep Neural Networks. CoRR abs/1905.11428 (2019) - [i5]Thiago Serra, Teng Huang, Arvind U. Raghunathan, David Bergman:
Template-based Minor Embedding for Adiabatic Quantum Optimization. CoRR abs/1910.02179 (2019) - 2018
- [i4]Thiago Serra, Christian Tjandraatmadja, Srikumar Ramalingam:
How Could Polyhedral Theory Harness Deep Learning? CoRR abs/1806.06365 (2018) - [i3]Egon Balas, Thiago Serra:
When Lift-and-Project Cuts are Different. CoRR abs/1809.05794 (2018) - [i2]Thiago Serra, Srikumar Ramalingam:
Empirical Bounds on Linear Regions of Deep Rectifier Networks. CoRR abs/1810.03370 (2018) - 2017
- [i1]Thiago Serra, Christian Tjandraatmadja, Srikumar Ramalingam:
Bounding and Counting Linear Regions of Deep Neural Networks. CoRR abs/1711.02114 (2017)
Coauthor Index
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