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Mayank Mishra
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2020 – today
- 2024
- [c39]Archisman Bhowmick
, Mayank Mishra
TASCA : Tool for Automatic SCalable Acceleration of ML pipelines✱. COMAD/CODS 2024: 514-518 - [c38]Harsh Rangwani, Pradipto Mondal, Pradipto Mondal, Mayank Mishra, Ashish Ramayee Asokan, R. Venkatesh Babu:
DeiT-LT: Distillation Strikes Back for Vision Transformer Training on Long-Tailed Datasets. CVPR 2024: 23396-23406 - [c37]Gaurav Pandey, Yatin Nandwani, Tahira Naseem, Mayank Mishra, Guangxuan Xu, Dinesh Raghu, Sachindra Joshi, Asim Munawar, Ramón Fernandez Astudillo:
BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback. ICML 2024 - [c36]Likhith Bandamudi
LLaMPS: Large Language Models Placement System. ICPE (Companion) 2024: 87-88 - [c35]Ravi Kumar Singh
Leftovers for LLaMA. ICPE 2024: 201-210 - [i24]Gaurav Pandey, Yatin Nandwani
BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback. CoRR abs/2402.02479 (2024) - [i23]Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu
StarCoder 2 and The Stack v2: The Next Generation. CoRR abs/2402.19173 (2024) - [i22]Taishi Nakamura, Mayank Mishra, Simone Tedeschi, Yekun Chai, Jason T. Stillerman, Felix Friedrich, Prateek Yadav, Tanmay Laud, Minh Chien Vu, Terry Yue Zhuo, Diganta Misra, Ben Bogin, Xuan-Son Vu, Marzena Karpinska, Arnav Varma Dantuluri, Wojciech Kusa, Tommaso Furlanello, Rio Yokota, Niklas Muennighoff, Suhas Pai, Tosin P. Adewumi, Veronika Laippala, Xiaozhe Yao, Adalberto Junior, Alpay Ariyak, Aleksandr Drozd, Jordan Clive, Kshitij Gupta, Liangyu Chen, Qi Sun, Ken Tsui, Noah Persaud, Nour Moustafa-Fahmy, Tianlong Chen, Mohit Bansal, Nicolo Monti, Tai Dang, Ziyang Luo, Tien-Tung Bui, Roberto Navigli, Virendra Mehta, Matthew Blumberg, Victor May, Huu Nguyen, Sampo Pyysalo:
Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order. CoRR abs/2404.00399 (2024) - [i21]Harsh Rangwani
DeiT-LT Distillation Strikes Back for Vision Transformer Training on Long-Tailed Datasets. CoRR abs/2404.02900 (2024) - [i20]Aniruddha Nrusimha, Mayank Mishra, Naigang Wang, Dan Alistarh, Rameswar Panda, Yoon Kim:
Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization. CoRR abs/2404.03605 (2024) - [i19]Bowen Pan, Yikang Shen, Haokun Liu, Mayank Mishra, Gaoyuan Zhang, Aude Oliva, Colin Raffel, Rameswar Panda:
Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models. CoRR abs/2404.05567 (2024) - [i18]Mayank Mishra, Matt Stallone, Gaoyuan Zhang, Yikang Shen, Aditya Prasad, Adriana Meza Soria, Michele Merler, Parameswaran Selvam, Saptha Surendran, Shivdeep Singh, Manish Sethi, Xuan-Hong Dang, Pengyuan Li, Kun-Lung Wu, Syed Zawad, Andrew Coleman, Matthew White, Mark Lewis, Raju Pavuluri, Yan Koyfman, Boris Lublinsky, Maximilien de Bayser, Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Yi Zhou, Chris Johnson, Aanchal Goyal, Hima Patel, S. Yousaf Shah, Petros Zerfos, Heiko Ludwig, Asim Munawar, Maxwell Crouse, Pavan Kapanipathi, Shweta Salaria, Bob Calio, Sophia Wen, Seetharami Seelam, Brian Belgodere, Carlos A. Fonseca, Amith Singhee, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda:
Granite Code Models: A Family of Open Foundation Models for Code Intelligence. CoRR abs/2405.04324 (2024) - [i17]William Brandon, Mayank Mishra, Aniruddha Nrusimha, Rameswar Panda, Jonathan Ragan-Kelley:
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention. CoRR abs/2405.12981 (2024) - [i16]Talia Gershon, Seetharami Seelam, Brian Belgodere, Milton Bonilla, Lan Hoang, Danny Barnett, I-Hsin Chung, Apoorve Mohan, Ming-Hung Chen, Lixiang Luo, Robert Walkup, Constantinos Evangelinos, Shweta Salaria, Marc Dombrowa, Yoonho Park, Apo Kayi, Liran Schour, Alim Alim, Ali Sydney, Pavlos Maniotis, Laurent Schares, Bernard Metzler, Bengi Karacali-Akyamac, Sophia Wen, Tatsuhiro Chiba, Sunyanan Choochotkaew, Takeshi Yoshimura, Claudia Misale, Tonia Elengikal, Kevin O. Connor, Zhuoran Liu, Richard Molina, Lars Schneidenbach, James Caden, Christopher Laibinis, Carlos Fonseca, Vasily Tarasov, Swaminathan Sundararaman, Frank B. Schmuck, Scott Guthridge, Jeremy Cohn, Marc Eshel, Paul Muench, Runyu Liu, William Pointer, Drew Wyskida, Bob Krull, Ray Rose, Brent Wolfe, William Cornejo, John Walter, Colm Malone, Clifford Perucci, Frank Franco, Nigel Hinds, Bob Calio, Pavel Druyan, Robert Kilduff, John Kienle, Connor McStay, Andrew Figueroa, Matthew Connolly, Edie Fost, Gina Roma, Jake Fonseca, Ido Levy, Michele Payne, Ryan Schenkel, Amir Malki, Lion Schneider, Aniruddha Narkhede, Shekeba Moshref, Alexandra Kisin, Olga Dodin, Bill Rippon, Henry Wrieth, John Ganci, Johnny Colino, Donna Habeger-Rose, Rakesh Pandey, Aditya Gidh, Aditya Gaur, Dennis Patterson, Samsuddin Salmani, Rambilas Varma, Rumana Rumana, Shubham Sharma, Mayank Mishra, Rameswar Panda, Aditya Prasad, Matt Stallone, Gaoyuan Zhang, Yikang Shen, David Cox, Ruchir Puri, Dakshi Agrawal, Drew Thorstensen, Joel Belog, Brent Tang:
The infrastructure powering IBM's Gen AI model development. CoRR abs/2407.05467 (2024) - [i15]Achintya Kundu, Rhui Dih Lee, Laura Wynter, Raghu Kiran Ganti, Mayank Mishra:
Enhancing Training Efficiency Using Packing with Flash Attention. CoRR abs/2407.09105 (2024) - [i14]Matt Stallone, Vaibhav Saxena, Leonid Karlinsky, Bridget McGinn, Tim Bula, Mayank Mishra, Adriana Meza Soria, Gaoyuan Zhang, Aditya Prasad, Yikang Shen, Saptha Surendran, Shanmukha C. Guttula, Hima Patel, Parameswaran Selvam, Xuan-Hong Dang, Yan Koyfman, Atin Sood, Rogério Feris, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda:
Scaling Granite Code Models to 128K Context. CoRR abs/2407.13739 (2024) - [i13]Yikang Shen, Matthew Stallone, Mayank Mishra, Gaoyuan Zhang, Shawn Tan, Aditya Prasad, Adriana Meza Soria, David D. Cox, Rameswar Panda:
Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Scheduler. CoRR abs/2408.13359 (2024) - [i12]Sonam Gupta, Yatin Nandwani, Asaf Yehudai, Mayank Mishra, Gaurav Pandey, Dinesh Raghu, Sachindra Joshi:
Selective Self-Rehearsal: A Fine-Tuning Approach to Improve Generalization in Large Language Models. CoRR abs/2409.04787 (2024) - 2023
- [j8]Mayank Mishra
A classification framework for Autism Spectrum Disorder detection using sMRI: Optimizer based ensemble of deep convolution neural network with on-the-fly data augmentation. Biomed. Signal Process. Control. 84: 104686 (2023) - [j7]Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, Qian Liu, Evgenii Zheltonozhskii, Terry Yue Zhuo, Thomas Wang, Olivier Dehaene, Mishig Davaadorj, Joel Lamy-Poirier, João Monteiro, Oleh Shliazhko, Nicolas Gontier, Nicholas Meade, Armel Zebaze, Ming-Ho Yee, Logesh Kumar Umapathi, Jian Zhu, Benjamin Lipkin, Muhtasham Oblokulov, Zhiruo Wang, Rudra Murthy V, Jason T. Stillerman, Siva Sankalp Patel, Dmitry Abulkhanov, Marco Zocca, Manan Dey, Zhihan Zhang, Nour Fahmy, Urvashi Bhattacharyya, Wenhao Yu, Swayam Singh, Sasha Luccioni, Paulo Villegas, Maxim Kunakov, Fedor Zhdanov, Manuel Romero, Tony Lee, Nadav Timor, Jennifer Ding, Claire Schlesinger, Hailey Schoelkopf, Jan Ebert, Tri Dao, Mayank Mishra, Alex Gu, Jennifer Robinson, Carolyn Jane Anderson, Brendan Dolan-Gavitt, Danish Contractor, Siva Reddy, Daniel Fried, Dzmitry Bahdanau, Yacine Jernite, Carlos Muñoz Ferrandis, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro von Werra, Harm de Vries:
StarCoder: may the source be with you! Trans. Mach. Learn. Res. 2023 (2023) - [c34]Mayank Mishra, Danish Contractor, Dinesh Raghu:
Joint Reasoning on Hybrid-knowledge sources for Task-Oriented Dialog. EACL (Findings) 2023: 1733-1742 - [c33]Mayank Mishra, Prince Kumar, Riyaz Bhat, Rudra Murthy V, Danish Contractor, Srikanth Tamilselvam:
Prompting with Pseudo-Code Instructions. EMNLP 2023: 15178-15197 - [c32]Ravi Kumar Singh
Scalable High-Performance Architecture for Evolving Recommender System. EuroMLSys@EuroSys 2023: 154-162 - [c31]Ravi Kumar Singh
Accelerating Model Training: Performance Antipatterns Eliminator Framework. EuroMLSys@EuroSys 2023: 163-170 - [i11]Loubna Ben Allal, Raymond Li, Denis Kocetkov, Chenghao Mou, Christopher Akiki, Carlos Muñoz Ferrandis, Niklas Muennighoff, Mayank Mishra, Alex Gu, Manan Dey, Logesh Kumar Umapathi, Carolyn Jane Anderson, Yangtian Zi, Joel Lamy-Poirier, Hailey Schoelkopf, Sergey Troshin, Dmitry Abulkhanov, Manuel Romero, Michael Lappert, Francesco De Toni, Bernardo García del Río, Qian Liu, Shamik Bose, Urvashi Bhattacharyya, Terry Yue Zhuo, Ian Yu, Paulo Villegas, Marco Zocca
SantaCoder: don't reach for the stars! CoRR abs/2301.03988 (2023) - [i10]Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, Qian Liu, Evgenii Zheltonozhskii, Terry Yue Zhuo, Thomas Wang, Olivier Dehaene, Mishig Davaadorj, Joel Lamy-Poirier, João Monteiro, Oleh Shliazhko, Nicolas Gontier, Nicholas Meade, Armel Zebaze, Ming-Ho Yee, Logesh Kumar Umapathi, Jian Zhu, Benjamin Lipkin
StarCoder: may the source be with you! CoRR abs/2305.06161 (2023) - [i9]Mayank Mishra, Prince Kumar, Riyaz Bhat, Rudra Murthy V, Danish Contractor, Srikanth Tamilselvam:
Prompting with Pseudo-Code Instructions. CoRR abs/2305.11790 (2023) - 2022
- [c30]Chetan Phalak, Mayank Mishra, Shruti Kunde, Rekha Singhal, Sana Iqbal:
Metamodel driven acceleration of actor-based simulation. BiDEDE@SIGMOD 2022: 3:1-3:8 - [c29]Dheeraj Chahal, Mayank Mishra, Surya Chaitanya Palepu, Ravi Kumar Singh, Rekha Singhal:
Pay-as-you-Train: Efficient ways of Serverless Training. IC2E 2022: 116-125 - [c28]Harsh Rangwani, Sumukh K. Aithal
A Closer Look at Smoothness in Domain Adversarial Training. ICML 2022: 18378-18399 - [c27]Mayank Mishra
Variational Learning for Unsupervised Knowledge Grounded Dialogs. IJCAI 2022: 4303-4309 - [c26]Harsh Rangwani, Sumukh K. Aithal, Mayank Mishra, Venkatesh Babu R.:
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data. NeurIPS 2022 - [c25]Chetan Phalak, Dheeraj Chahal, Aniruddha Sen, Mayank Mishra, Rekha Singhal:
MAPLE: Model Aggregation and Prediction for Learned Ecosystem. ICPE (Companion) 2022: 17-18 - [i8]Harsh Rangwani, Sumukh K. Aithal, Mayank Mishra, Arihant Jain, R. Venkatesh Babu
A Closer Look at Smoothness in Domain Adversarial Training. CoRR abs/2206.08213 (2022) - [i7]Mayank Mishra, Danish Contractor, Dinesh Raghu:
Joint Reasoning on Hybrid-knowledge sources for Task-Oriented Dialog. CoRR abs/2210.07295 (2022) - [i6]Harsh Rangwani, Sumukh K. Aithal, Mayank Mishra, R. Venkatesh Babu:
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data. CoRR abs/2212.13827 (2022) - 2021
- [j6]Mayank Mishra
A comparative study of regression, neural network and neuro-fuzzy inference system for determining the compressive strength of brick-mortar masonry by fusing nondestructive testing data. Eng. Comput. 37(1): 77-91 (2021) - [c24]Mayank Mishra, Rekha Singhal, Ravi Singh
Towards Accelerating Offline RL based Recommender Systems. AIMLSystems 2021: 24:1-24:7 - [c23]Mayank Mishra, Archisman Bhowmick, Rekha Singhal:
FASCA: Framework for Automatic Scalable Acceleration of ML Pipeline. IEEE BigData 2021: 1867-1876 - [c22]Tejas Dubhir, Mayank Mishra, Rekha Singhal:
Benchmarking of Quantization Libraries in Popular Frameworks. IEEE BigData 2021: 3050-3055 - [c21]Dheeraj Chahal, Surya Palepu
SLA-aware Workload Scheduling Using Hybrid Cloud Services. HiPS@HPDC 2021: 1-4 - [c20]Mayank Mishra, Rekha Singhal:
RUSLI: Real-time Updatable Spline Learned Index. aiDM@SIGMOD 2021: 1-8 - [c19]Shruti Kunde, Amey Pandit, Mayank Mishra, Rekha Singhal:
Distributed training for accelerating metalearning algorithms. BiDEDE@SIGMOD 2021: 2:1-2:6 - [c18]Dheeraj Chahal, Mayank Mishra, Surya Palepu
Performance and Cost Comparison of Cloud Services for Deep Learning Workload. ICPE (Companion) 2021: 49-55 - [i5]Varad Pimpalkhute
Accelerating Gradient-based Meta Learner. CoRR abs/2110.14459 (2021) - [i4]Mayank Mishra, Dhiraj Madan, Gaurav Pandey, Danish Contractor:
Variational Learning for Unsupervised Knowledge Grounded Dialogs. CoRR abs/2112.00653 (2021) - 2020
- [j5]Mayank Mishra
Performance Studies of 10 Metaheuristic Techniques in Determination of Damages for Large-Scale Spatial Trusses from Changes in Vibration Responses. J. Comput. Civ. Eng. 34(2) (2020) - [j4]Mayank Mishra
Teaching-learning-based optimisation algorithm and its application in capturing critical slip surface in slope stability analysis. Soft Comput. 24(4): 2969-2982 (2020) - [c17]Shruti Kunde, Mayank Mishra, Amey Pandit, Rekha Singhal, Manoj Karunakaran Nambiar, Gautam Shroff, Shashank Gupta
Recommending in changing times. RecSys 2020: 714-719 - [c16]Rekha Singhal, Dheeraj Chahal, Shruti Kunde, Mayank Mishra, Manoj Nambiar:
A Vision on Accelerating Enterprise IT System 2.0. DEEM@SIGMOD 2020: 8:1-8:9
2010 – 2019
- 2019
- [j3]Varun Srivastava
Adversarial Approximate Inference for Speech to Electroglottograph Conversion. IEEE ACM Trans. Audio Speech Lang. Process. 27(12): 2183-2196 (2019) - [c15]Debanshu Biswas, Ipsit Nayak, Shaibal Choudhury, Trishaani Acharjee, Sidhant, Mayank Mishra
Crack Detection on Inner Tunnel Surface Using Image Processing. ICACIE (1) 2019: 3-12 - [i3]Prathosh A. P., Varun Srivastava, Mayank Mishra:
Adversarial Approximate Inference for Speech to Electroglottograph Conversion. CoRR abs/1903.12248 (2019) - 2018
- [c14]Mayank Mishra, Shruti Kunde, Manoj Nambiar:
Cracking the monolith: challenges in data transitioning to cloud native architectures. ECSA (Companion) 2018: 35:1-35:4 - [c13]Mayank Mishra, Satyabrata Aich, Hee-Cheol Kim, Pyari Mohan Pradhan:
A Novel Ramp-based Pulse Shaping Filter for Reducing Out of Band Emission in 5G GFDM System. TENCON 2018: 96-101 - 2017
- [c12]Piyush Lakhawat, Mayank Mishra, Arun K. Somani:
A Clustering based Prediction Scheme for High Utility Itemsets. KDIR 2017: 123-134 - [i2]Mayank Mishra, Arun K. Somani:
On-Disk Data Processing: Issues and Future Directions. CoRR abs/1709.02718 (2017) - 2016
- [j2]Mayank Mishra, Umesh Bellur:
Whither Tightness of Packing? The Case for Stable VM Placement. IEEE Trans. Cloud Comput. 4(4): 481-494 (2016) - [c11]Mayank Mishra, Umesh Bellur:
De-Fragmenting the Cloud. CCGrid 2016: 511-520 - [c10]Piyush Lakhawat, Mayank Mishra, Arun K. Somani:
A Novel Clustering Algorithm to Capture Utility Information in Transactional Data. KDIR 2016: 456-462 - [c9]Pratik Mishra, Mayank Mishra, Arun K. Somani:
Bulk I/O Storage Management for Big Data Applications. MASCOTS 2016: 412-417 - 2015
- [i1]Mayank Mishra, Umesh Bellur:
De-Fragmenting the Cloud. CoRR abs/1506.07020 (2015) - 2013
- [c8]Mayank Mishra, Partha Dutta, Praveen Kumar, Vijay Mann:
Managing Network Reservation for Tenants in Oversubscribed Clouds. MASCOTS 2013: 50-59 - 2012
- [j1]Mayank Mishra, Anwesha Das, Purushottam Kulkarni, Anirudha Sahoo:
Dynamic resource management using virtual machine migrations. IEEE Commun. Mag. 50(9): 34-40 (2012) - [c7]Dhaval Manvar, Mayank Mishra, Anirudha Sahoo:
Low cost computing using virtualization for Remote Desktop. COMSNETS 2012: 1-2 - 2011
- [c6]Mayank Mishra, Anirudha Sahoo:
On Theory of VM Placement: Anomalies in Existing Methodologies and Their Mitigation Using a Novel Vector Based Approach. IEEE CLOUD 2011: 275-282
2000 – 2009
- 2009
- [c5]Mayank Mishra, Hemant A. Patil:
Design and Implementation of HMM-VQ based Isolated Digit Recognition System. IICAI 2009: 1754-1763 - 2007
- [c4]Mayank Mishra, Anirudha Sahoo:
An 802.11 Based MAC Protocol for Providing QoS to Real Time Applications. ICIT 2007: 104-109 - 2006
- [c3]Mayank Mishra, Anirudha Sahoo:
A Contention Window Based Differentiation Mechanism for providing QoS in Wireless LANs. ICIT 2006: 72-76 - 2005
- [c2]Mayank Mishra, Sanjay Chaudhary
Design and implementation of an architecture supporting mobile CORBA servants under intermittent connectivity environment. WCNC 2005: 2418-2423 - 2004
- [c1]Mayank Mishra:
Architecture for Locating Mobile CORBA Objects in Wireless Mobile Environment. ISSADS 2004: 207-218
Coauthor Index
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