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Sunil Thulasidasan
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Journal Articles
- 2016
- [j4]Richard J. Zamora
, Arthur F. Voter, Danny Perez, Nandakishore Santhi
Discrete event performance prediction of speculatively parallel temperature-accelerated dynamics. Simul. 92(12): 1065-1086 (2016) - 2015
- [j3]Hristo N. Djidjev
All-Pairs Shortest Path algorithms for planar graph for GPU-accelerated clusters. J. Parallel Distributed Comput. 85: 91-103 (2015) - 2010
- [j2]Guanhua Yan, Stephan J. Eidenbenz
Criticality analysis of Internet infrastructure. Comput. Networks 54(7): 1169-1182 (2010) - 2004
- [j1]Mark K. Gardner, Sunil Thulasidasan, Wu-chun Feng:
User-space auto-tuning for TCP flow control in computational grids. Comput. Commun. 27(14): 1364-1374 (2004)
Conference and Workshop Papers
- 2023
- [c23]Dhruv Tulasi, Alys Granados, Prabath Gunawardane, Abhay Kashyap, Zara McDonald, Sunil Thulasidasan:
Smart Camera Traps: Enabling Energy-Efficient Edge-AI for Remote Monitoring of Wildlife. GeoWildLife@SIGSPATIAL 2023: 9-16 - 2021
- [c22]Sunil Thulasidasan, Sushil Thapa, Sayera Dhaubhadel, Gopinath Chennupati, Tanmoy Bhattacharya, Jeff A. Bilmes:
An Effective Baseline for Robustness to Distributional Shift. ICMLA 2021: 278-285 - 2019
- [c21]Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff A. Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof:
Combating Label Noise in Deep Learning using Abstention. ICML 2019: 6234-6243 - [c20]Sunil Thulasidasan, Gopinath Chennupati, Jeff A. Bilmes, Tanmoy Bhattacharya, Sarah Michalak:
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. NeurIPS 2019: 13888-13899 - 2017
- [c19]Gopinath Chennupati
AMM: Scalable Memory Reuse Model to Predict the Performance of Physics Codes. CLUSTER 2017: 649-650 - [c18]Sunil Thulasidasan, Jeffrey A. Bilmes:
Acoustic classification using semi-supervised Deep Neural Networks and stochastic entropy-regularization over nearest-neighbor graphs. ICASSP 2017: 2731-2735 - [c17]Gopinath Chennupati, Nandakishore Santhi
A Scalable Analytical Memory Model for CPU Performance Prediction. PMBS@SC 2017: 114-135 - [c16]Gopinath Chennupati, Nandakishore Santhi
An analytical memory hierarchy model for performance prediction. WSC 2017: 908-919 - 2016
- [c15]Jiangzhuo Chen, V. S. Anil Kumar, Madhav V. Marathe, Ravi Sundaram, Mayur Thakur, Sunil Thulasidasan:
A study of the structure and vulnerabilities of metropolitan area networks. COMSNETS 2016: 1-8 - [c14]Chandrashekhar Lavania, Sunil Thulasidasan, Anthony LaMarca, Jeffrey Scofield, Jeff A. Bilmes:
A weakly supervised activity recognition framework for real-time synthetic biology laboratory assistance. UbiComp 2016: 37-48 - 2014
- [c13]M. S. Srinivasan, Srinath Srinivasa, Sunil Thulasidasan:
A comparative study of two models for celebrity identification on Twitter. COMAD 2014: 57-65 - [c12]Hristo N. Djidjev
Efficient Multi-GPU Computation of All-Pairs Shortest Paths. IPDPS 2014: 360-369 - [c11]Sunil Thulasidasan, Lukas Kroc, Stephan J. Eidenbenz:
Developing parallel, discrete event simulations in Python - first results and user experiences with the SimX library. SIMULTECH 2014: 188-194 - 2012
- [c10]Sunil Thulasidasan, Lukas Kroc, Stephan J. Eidenbenz:
SimCore: A Library for Rapid Development of Large Scale Parallel Simulations. SIMULTECH 2012: 71-76 - 2011
- [c9]Sunil Thulasidasan:
Heuristic acceleration of routing in transportation simulations using GPUs. SimuTools 2011: 90-92 - 2010
- [c8]Sunil Thulasidasan, Shiva Prasad Kasiviswanathan, Stephan J. Eidenbenz
Explicit Spatial Scattering for Load Balancing in Conservatively Synchronized Parallel Discrete Event Simulations. PADS 2010: 150-157 - 2009
- [c7]Sunil Thulasidasan, Shiva Prasad Kasiviswanathan, Stephan J. Eidenbenz
Designing systems for large-scale, discrete-event simulations: Experiences with the FastTrans parallel microsimulator. HiPC 2009: 428-437 - [c6]Russell Bent, Stephan J. Eidenbenz, Sunil Thulasidasan:
Large-scale telephone network simulation: discrete event vs. steady state. SpringSim 2009 - [c5]Sunil Thulasidasan, Stephan J. Eidenbenz
Accelerating Traffic Microsimulations: A Parallel Discrete-event Queue-based Approach for Speed and Scale. WSC 2009: 2457-2466 - 2006
- [c4]Gabriel Istrate, Anders Hansson, Sunil Thulasidasan, Madhav V. Marathe, Christopher L. Barrett:
Semantic Compression of TCP Traces. Networking 2006: 123-135 - 2003
- [c3]Sunil Thulasidasan, Wu-chun Feng, Mark K. Gardner:
Optimizing GridFTP through Dynamic Right-Sizing. HPDC 2003: 14-23 - 2002
- [c2]Wu-chun Feng, Apu Kapadia, Sunil Thulasidasan:
GREEN: proactive queue management over a best-effort network. GLOBECOM 2002: 1774-1778 - [c1]Sunil Thulasidasan, Wu-chun Feng:
Using Steady- State TCP Behavior for Proactive Queue Management. International Conference on Internet Computing 2002: 371-378
Informal and Other Publications
- 2021
- [i7]Sunil Thulasidasan, Sushil Thapa, Sayera Dhaubhadel, Gopinath Chennupati, Tanmoy Bhattacharya, Jeff A. Bilmes:
An Effective Baseline for Robustness to Distributional Shift. CoRR abs/2105.07107 (2021) - 2020
- [i6]Sayera Dhaubhadel, Jamaludin Mohd-Yusof, Kumkum Ganguly, Gopinath Chennupati, Sunil Thulasidasan, Nicolas W. Hengartner, Brent J. Mumphrey, Eric B. Durbin, Jennifer A. Doherty, Mireille Lemieux, Noah Schaefferkoetter, Georgia D. Tourassi, Linda Coyle, Lynne Penberthy, Benjamin McMahon, Tanmoy Bhattacharya:
Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports. CoRR abs/2009.05094 (2020) - [i5]Xiaoying Pang, Sunil Thulasidasan, Larry Rybarcyk:
Autonomous Control of a Particle Accelerator using Deep Reinforcement Learning. CoRR abs/2010.08141 (2020) - 2019
- [i4]Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff A. Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof:
Combating Label Noise in Deep Learning Using Abstention. CoRR abs/1905.10964 (2019) - [i3]Sunil Thulasidasan, Gopinath Chennupati, Jeff A. Bilmes, Tanmoy Bhattacharya, Sarah Michalak:
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. CoRR abs/1905.11001 (2019) - 2016
- [i2]Sunil Thulasidasan, Jeffrey A. Bilmes, Garrett T. Kenyon:
Efficient Distributed Semi-Supervised Learning using Stochastic Regularization over Affinity Graphs. CoRR abs/1612.04898 (2016) - [i1]Sunil Thulasidasan, Jeffrey A. Bilmes:
Semi-Supervised Phone Classification using Deep Neural Networks and Stochastic Graph-Based Entropic Regularization. CoRR abs/1612.04899 (2016)
Coauthor Index
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