Khoa Trinh

29 papers A* 7A 2Journal 15Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
GUIDE: Guided Initialization and Distillation of Embeddings.
CoRR
Khoa Trinh, Gaurav Menghani, Erik Vee
2023 A* conf
Improved Bi-point Rounding Algorithms and a Golden Barrier for
SODA
Kishen N. Gowda, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2023 A* conf
Robust Active Distillation.
ICLR
Cenk Baykal, Khoa Trinh, Fotis Iliopoulos, Gaurav Menghani, Erik Vee
2023 A* conf
SLaM: Student-Label Mixing for Distillation with Unlabeled Examples.
NeurIPS
Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee
2023 J jnl
SLaM: Student-Label Mixing for Semi-Supervised Knowledge Distillation.
CoRR
Vasilis Kontonis, Fotis Iliopoulos, Khoa Trinh, Cenk Baykal, Gaurav Menghani, Erik Vee
2022 J jnl
Dependent randomized rounding for clustering and partition systems with knapsack constraints.
J. Mach. Learn. Res.
David G. Harris, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2022 J jnl
Improved Bi-point Rounding Algorithms and a Golden Barrier for k-Median.
CoRR
Kishen N. Gowda, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2022 J jnl
Robust Active Distillation.
CoRR
Cenk Baykal, Khoa Trinh, Fotis Iliopoulos, Gaurav Menghani, Erik Vee
2022 A* conf
Weighted Distillation with Unlabeled Examples.
NeurIPS
Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh, Erik Vee
2022 J jnl
Weighted Distillation with Unlabeled Examples.
CoRR
Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh, Erik Vee
2020 A conf
Dependent randomized rounding for clustering and partition systems with knapsack constraints.
AISTATS
David G. Harris, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2019 J jnl
A Lottery Model for Center-Type Problems With Outliers.
ACM Trans. Algorithms
David G. Harris, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2019 J jnl
Approximation Algorithms for Stochastic Clustering.
J. Mach. Learn. Res.
David G. Harris, Shi Li, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2018 J jnl
An Improved Approximation Algorithm for Knapsack Median Using Sparsification.
Algorithmica
Jaroslaw Byrka, Thomas W. Pensyl, Bartosz Rybicki, Joachim Spoerhase, Aravind Srinivasan, Khoa Trinh
2018 A* conf
Approximation algorithms for stochastic clustering.
NeurIPS
David G. Harris, Shi Li, Aravind Srinivasan, Khoa Trinh, Thomas W. Pensyl
2018 J jnl
Approximation algorithms for stochastic clustering.
CoRR
David G. Harris, Shi Li, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2017 — conf
A Lottery Model for Center-Type Problems with Outliers.
APPROX-RANDOM
David G. Harris, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2017 J jnl
A Lottery Model for Center-type Problems With Outliers.
CoRR
David G. Harris, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2017 J jnl
An Improved Approximation for
ACM Trans. Algorithms
Jaroslaw Byrka, Thomas W. Pensyl, Bartosz Rybicki, Aravind Srinivasan, Khoa Trinh
2017 — —
Approximation Algorithms for Facility Location and Clustering Problems.
Khoa Trinh
2017 J jnl
Symmetric Randomized Dependent Rounding.
CoRR
David G. Harris, Thomas W. Pensyl, Aravind Srinivasan, Khoa Trinh
2015 A conf
An Improved Approximation Algorithm for Knapsack Median Using Sparsification.
ESA
Jaroslaw Byrka, Thomas W. Pensyl, Bartosz Rybicki, Joachim Spoerhase, Aravind Srinivasan, Khoa Trinh
2015 A* conf
An Improved Approximation for
SODA
Jaroslaw Byrka, Thomas W. Pensyl, Bartosz Rybicki, Aravind Srinivasan, Khoa Trinh
2014 J jnl
'Beating the news' with EMBERS: Forecasting Civil Unrest using Open Source Indicators.
CoRR
Naren Ramakrishnan, Patrick Butler, Sathappan Muthiah, Nathan Self, Rupinder Paul Khandpur, Parang Saraf, Wei Wang, Jose Cadena, Anil Vullikanti, Gizem Korkmaz, Chris J. Kuhlman, Achla Marathe, Liang Zhao, Ting Hua, Feng Chen, Chang-Tien Lu, Bert Huang, Aravind Srinivasan, Khoa Trinh, Lise Getoor, Graham Katz, Andy Doyle, Chris Ackermann, Ilya Zavorin, Jim Ford, Kristen Maria Summers, Youssef Fayed, Jaime Arredondo, Dipak Gupta, David Mares
2014 A* conf
'Beating the news' with EMBERS: forecasting civil unrest using open source indicators.
KDD
Naren Ramakrishnan, Patrick Butler, Sathappan Muthiah, Nathan Self, Rupinder Paul Khandpur, Parang Saraf, Wei Wang, Jose Cadena, Anil Vullikanti, Gizem Korkmaz, Chris J. Kuhlman, Achla Marathe, Liang Zhao, Ting Hua, Feng Chen, Chang-Tien Lu, Bert Huang, Aravind Srinivasan, Khoa Trinh, Lise Getoor, Graham Katz, Andy Doyle, Chris Ackermann, Ilya Zavorin, Jim Ford, Kristen Maria Summers, Youssef Fayed, Jaime Arredondo, Dipak Gupta, David Mares
2014 J jnl
An Improved Approximation for $k$-median, and Positive Correlation in Budgeted Optimization.
CoRR
Jaroslaw Byrka, Thomas W. Pensyl, Bartosz Rybicki, Aravind Srinivasan, Khoa Trinh
2011 — conf
A Stochastic Optimization Method for Solving the Machine-Part Cell Formation Problem.
ICIC (1)
Khoa Trinh, Jacques A. Ferland, Tien Ba Dinh
2011 — conf
An Approximation Approach for a Real-World Variant of Vehicle Routing Problem.
ACIIDS Posters
Khoa Trinh, Nguyen Dang, Tien Ba Dinh
2008 — conf
An empirical study of multipass decoding for vietnamese LVCSR.
SLTU
Khoa Trinh, Ha Nguyen, Duc Duong, Quan Vu