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ORCIDManish Purohit
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2020 – today
- 2024
[c30]Sungjin Im
, Ravi Kumar, Shi Li, Aditya Petety, Manish Purohit:
Online Load and Graph Balancing for Random Order Inputs. SPAA 2024: 491-497- [i23]Sungjin Im, Ravi Kumar, Shi Li, Aditya Petety, Manish Purohit:
Online Load and Graph Balancing for Random Order Inputs. CoRR abs/2405.07949 (2024) - [i22]Ravi Kumar, Manish Purohit, Zoya Svitkina:
Improving Online Algorithms via ML Predictions. CoRR abs/2407.17712 (2024) - 2023
- [j8]Priyanka Shende, Manish Purohit:
Strategy-proof and envy-free mechanisms for house allocation. J. Econ. Theory 213: 105712 (2023) - [j7]Sungjin Im, Ravi Kumar, Mahshid Montazer Qaem, Manish Purohit:
Non-clairvoyant Scheduling with Predictions. ACM Trans. Parallel Comput. 10(4): 19:1-19:26 (2023) - [c29]Sharat Ibrahimpur, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang:
Efficient Caching with Reserves via Marking. ICALP 2023: 80:1-80:20 - [c28]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Bandit Online Linear Optimization with Hints and Queries. ICML 2023: 2313-2336 - [i21]Sharat Ibrahimpur, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang:
Efficient Caching with Reserves via Marking. CoRR abs/2305.02508 (2023) - [i20]Pengming Wang, Mikita Sazanovich, Berkin Ilbeyi, Phitchaya Mangpo Phothilimthana, Manish Purohit, Han Yang Tay, Ngân Vu, Miaosen Wang, Cosmin Paduraru, Edouard Leurent, Anton Zhernov, Julian Schrittwieser, Thomas Hubert, Robert Tung, Paula Kurylowicz, Kieran Milan, Oriol Vinyals, Daniel J. Mankowitz:
Optimizing Memory Mapping Using Deep Reinforcement Learning. CoRR abs/2305.07440 (2023) - [i19]Ce Jin, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang:
New Tools for Peak Memory Scheduling. CoRR abs/2312.13526 (2023) - 2022
- [c27]Sharat Ibrahimpur, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang:
Caching with Reserves. APPROX/RANDOM 2022: 52:1-52:16 - [c26]Sungjin Im, Ravi Kumar, Aditya Petety, Manish Purohit:
Parsimonious Learning-Augmented Caching. ICML 2022: 9588-9601 - [c25]Nikhil Bansal, Christian Coester, Ravi Kumar, Manish Purohit, Erik Vee:
Learning-Augmented Weighted Paging. SODA 2022: 67-89 - [c24]Quanquan C. Liu, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang:
Scheduling with Communication Delay in Near-Linear Time. STACS 2022: 47:1-47:23 - [i18]Sungjin Im, Ravi Kumar, Aditya Petety, Manish Purohit:
Parsimonious Learning-Augmented Caching. CoRR abs/2202.04262 (2022) - [i17]Sharat Ibrahimpur, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang:
Caching with Reserves. CoRR abs/2207.05975 (2022) - 2021
- [c23]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Power of Hints for Online Learning with Movement Costs. AISTATS 2021: 2818-2826 - [c22]Kshipra Bhawalkar, Kostas Kollias, Manish Purohit:
Revenue Maximization in Transportation Networks. APPROX-RANDOM 2021: 26:1-26:16 - [c21]Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit:
Dynamic Balancing for Model Selection in Bandits and RL. ICML 2021: 2276-2285 - [c20]Sungjin Im, Ravi Kumar, Mahshid Montazer Qaem, Manish Purohit:
Online Knapsack with Frequency Predictions. NeurIPS 2021: 2733-2743 - [c19]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Logarithmic Regret from Sublinear Hints. NeurIPS 2021: 28222-28232 - [c18]Sungjin Im, Ravi Kumar, Mahshid Montazer Qaem, Manish Purohit:
Non-Clairvoyant Scheduling with Predictions. SPAA 2021: 285-294 - [i16]Quanquan C. Liu, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang:
Scheduling with Communication Delay in Near-Linear Time. CoRR abs/2108.02770 (2021) - [i15]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Logarithmic Regret from Sublinear Hints. CoRR abs/2111.05257 (2021) - [i14]Sagnik Saha, Manish Purohit:
NP-completeness of the Active Time Scheduling Problem. CoRR abs/2112.03255 (2021) - 2020
- [j6]Saba Ahmadi, Samir Khuller, Manish Purohit, Sheng Yang:
On Scheduling Coflows. Algorithmica 82(12): 3604-3629 (2020) - [j5]Samir Khuller, Manish Purohit, Kanthi K. Sarpatwar:
Analyzing the Optimal Neighborhood: Algorithms for Partial and Budgeted Connected Dominating Set Problems. SIAM J. Discret. Math. 34(1): 251-270 (2020) - [j4]MohammadTaghi Hajiaghayi, Guy Kortsarz, Robert MacDavid, Manish Purohit, Kanthi K. Sarpatwar:
Approximation algorithms for connected maximum cut and related problems. Theor. Comput. Sci. 814: 74-85 (2020) - [c17]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Learning with Imperfect Hints. ICML 2020: 822-831 - [c16]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Linear Optimization with Many Hints. NeurIPS 2020 - [c15]Ravi Kumar, Manish Purohit, Zoya Svitkina, Erik Vee:
Interleaved Caching with Access Graphs. SODA 2020: 1846-1858 - [i13]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Learning with Imperfect Hints. CoRR abs/2002.04726 (2020) - [i12]Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit:
Online Linear Optimization with Many Hints. CoRR abs/2010.03082 (2020) - [i11]Nikhil Bansal, Christian Coester, Ravi Kumar, Manish Purohit, Erik Vee:
Scale-Free Allocation, Amortized Convexity, and Myopic Weighted Paging. CoRR abs/2011.09076 (2020) - [i10]Ashok Cutkosky, Abhimanyu Das, Manish Purohit:
Upper Confidence Bounds for Combining Stochastic Bandits. CoRR abs/2012.13115 (2020)
2010 – 2019
- 2019
- [c14]Sungjin Im, Benjamin Moseley, Kirk Pruhs, Manish Purohit:
Matroid Coflow Scheduling. ICALP 2019: 145:1-145:14 - [c13]Manish Purohit, Sreenivas Gollapudi, Manish Raghavan:
Hiring Under Uncertainty. ICML 2019: 5181-5189 - [c12]Ravi Kumar, Manish Purohit, Aaron Schild, Zoya Svitkina, Erik Vee:
Semi-Online Bipartite Matching. ITCS 2019: 50:1-50:20 - [c11]Ravi Kumar, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang:
Efficient Rematerialization for Deep Networks. NeurIPS 2019: 15146-15155 - [c10]Mosharaf Chowdhury, Samir Khuller, Manish Purohit, Sheng Yang, Jie You:
Near Optimal Coflow Scheduling in Networks. SPAA 2019: 123-134 - [i9]Manish Raghavan, Manish Purohit, Sreenivas Gollapudi:
Hiring Under Uncertainty. CoRR abs/1905.02709 (2019) - [i8]Mosharaf Chowdhury, Samir Khuller, Manish Purohit, Sheng Yang, Jie You:
Near Optimal Coflow Scheduling in Networks. CoRR abs/1906.06851 (2019) - 2018
- [j3]Rajiv Gandhi, Mohammad Taghi Hajiaghayi, Guy Kortsarz, Manish Purohit, Kanthi K. Sarpatwar:
On maximum leaf trees and connections to connected maximum cut problems. Inf. Process. Lett. 129: 31-34 (2018) - [c9]Manish Purohit, Zoya Svitkina, Ravi Kumar:
Improving Online Algorithms via ML Predictions. NeurIPS 2018: 9684-9693 - [i7]Ravi Kumar, Manish Purohit, Aaron Schild, Zoya Svitkina, Erik Vee:
Semi-Online Bipartite Matching. CoRR abs/1812.00134 (2018) - 2017
- [j2]Sreyash Kenkre, Vinayaka Pandit, Manish Purohit, Rishi Saket:
On the Approximability of Digraph Ordering. Algorithmica 78(4): 1182-1205 (2017) - [c8]Saba Ahmadi, Samir Khuller, Manish Purohit, Sheng Yang:
On Scheduling Coflows - (Extended Abstract). IPCO 2017: 13-24 - [i6]Sungjin Im, Manish Purohit:
A Tight Approximation for Co-flow Scheduling for Minimizing Total Weighted Completion Time. CoRR abs/1707.04331 (2017) - 2016
- [b1]Manish Purohit:
Data-Aware Scheduling in Datacenters. University of Maryland, College Park, MD, USA, 2016 - [c7]Samir Khuller, Manish Purohit:
Brief Announcement: Improved Approximation Algorithms for Scheduling Co-Flows. SPAA 2016: 239-240 - 2015
- [c6]Mohammad Taghi Hajiaghayi, Guy Kortsarz, Robert MacDavid, Manish Purohit, Kanthi K. Sarpatwar:
Approximation Algorithms for Connected Maximum Cut and Related Problems. ESA 2015: 693-704 - [c5]Sreyash Kenkre, Vinayaka Pandit, Manish Purohit, Rishi Saket:
On the Approximability of Digraph Ordering. ESA 2015: 792-803 - [c4]Hal Daumé III, Samir Khuller, Manish Purohit, Gregory Sanders:
On Correcting Inputs: Inverse Optimization for Online Structured Prediction. FSTTCS 2015: 38-51 - [i5]MohammadTaghi Hajiaghayi, Guy Kortsarz, Robert MacDavid, Manish Purohit, Kanthi K. Sarpatwar:
Approximation Algorithms for Connected Maximum Cut and Related Problems. CoRR abs/1507.00648 (2015) - [i4]Sreyash Kenkre, Vinayaka Pandit, Manish Purohit, Rishi Saket:
On the Approximability of Digraph Ordering. CoRR abs/1507.00662 (2015) - [i3]Hal Daumé III, Samir Khuller, Manish Purohit, Gregory Sanders:
On Correcting Inputs: Inverse Optimization for Online Structured Prediction. CoRR abs/1510.03130 (2015) - 2014
- [c3]Manish Purohit, B. Aditya Prakash, Chanhyun Kang, Yao Zhang, V. S. Subrahmanian:
Fast influence-based coarsening for large networks. KDD 2014: 1296-1305 - [c2]Samir Khuller, Manish Purohit, Kanthi K. Sarpatwar:
Analyzing the Optimal Neighborhood: Algorithms for Budgeted and Partial Connected Dominating Set Problems. SODA 2014: 1702-1713 - 2013
- [j1]Rami Puzis, Manish Purohit, V. S. Subrahmanian:
Betweenness computation in the single graph representation of hypergraphs. Soc. Networks 35(4): 561-572 (2013) - [c1]Seungjoon Lee, Manish Purohit, Barna Saha:
Firewall placement in cloud data centers. SoCC 2013: 52:1-52:2 - [i2]David G. Harris, Manish Purohit:
Improved algorithms and analysis for the laminar matroid secretary problem. CoRR abs/1301.4958 (2013) - [i1]Samir Khuller, Manish Purohit, Kanthi K. Sarpatwar:
Analyzing the Optimal Neighborhood: Algorithms for Budgeted and Partial Connected Dominating Set Problems. CoRR abs/1311.2309 (2013)
Coauthor Index
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last updated on 2024-08-27 22:53 CEST by the dblp team
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