Ankur Mallick

According to our database, Ankur Mallick authored at least 24 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Tetris: Efficient Intra-Datacenter Calls Packing for Large Conferencing Services.

Rohan Gandhi, Ankur Mallick, Ken Sueda, Rui Liang

CoRR, August, 2025

BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute.

Dujian Ding, Ankur Mallick, Shaokun Zhang, Chi Wang, Daniel Madrigal, Mirian del Carmen Hipolito Garcia, Menglin Xia, Laks V. S. Lakshmanan, Qingyun Wu, Victor Rühle

CoRR, June, 2025

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search.

Dongge Han, Menglin Xia, Daniel Madrigal Diaz, Samuel Kessler, Ankur Mallick, Xuchao Zhang, Mirian del Carmen Hipolito Garcia, Jin Xu, Victor Rühle, Saravan Rajmohan

CoRR, June, 2025

Exploring How LLMs Capture and Represent Domain-Specific Knowledge.

Mirian Hipolito Garcia, Camille Couturier, Daniel Madrigal Diaz, Ankur Mallick, Anastasios Kyrillidis, Robert Sim, Victor Rühle, Saravan Rajmohan

CoRR, April, 2025

Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale.

Shashwat Jaiswal, Kunal Jain, Yogesh Simmhan, Anjaly Parayil, Ankur Mallick, Rujia Wang, Renée St. Amant, Chetan Bansal, Victor Rühle, Anoop Kulkarni, Steve Kofsky, Saravan Rajmohan

CoRR, February, 2025

Performance Aware LLM Load Balancer for Mixed Workloads.

Kunal Jain, Anjaly Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Rühle, Anoop Kulkarni, Steve Kofsky, Saravan Rajmohan

Proceedings of the 5th Workshop on Machine Learning and Systems, 2025

2024

Ensuring Fair LLM Serving Amid Diverse Applications.

Redwan Ibne Seraj Khan, Kunal Jain, Haiying Shen, Ankur Mallick, Anjaly Parayil, Anoop Kulkarni, Steve Kofsky, Pankhuri Choudhary, Renée St. Amant, Rujia Wang, Yue Cheng, Ali Raza Butt, Victor Rühle, Chetan Bansal, Saravan Rajmohan

CoRR, 2024

EcoAct: Economic Agent Determines When to Register What Action.

Shaokun Zhang, Jieyu Zhang, Dujian Ding, Mirian Hipolito Garcia, Ankur Mallick, Daniel Madrigal, Menglin Xia, Victor Rühle, Qingyun Wu, Chi Wang

CoRR, 2024

Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling.

Kunal Jain, Anjaly Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Rühle, Anoop Kulkarni, Steve Kofsky, Saravan Rajmohan

CoRR, 2024

Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing.

Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Rühle, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Probabilistic Methods for Mitigating Uncertainties in Large-Scale Computing and Machine Learning

Ankur Mallick

PhD thesis, 2023

2022

Matchmaker: Data Drift Mitigation in Machine Learning for Large-Scale Systems.

Ankur Mallick, Kevin Hsieh, Behnaz Arzani, Gauri Joshi

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

Rateless Sum-Recovery Codes For Distributed Non-Linear Computations.

Ankur Mallick, Gauri Joshi

Proceedings of the IEEE Information Theory Workshop, 2022

2021

Deep kernels with probabilistic embeddings for small-data learning.

Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, Thomas Yong-Jin Han

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation.

Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar, Swanand Kadhe, Gauri Joshi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Rateless Codes for Distributed Non-linear Computations.

Ankur Mallick, Sophie Smith, Gauri Joshi

Proceedings of the 11th International Symposium on Topics in Coding, 2021

2020

Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning.

Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, Thomas Yong-Jin Han

CoRR, 2020

2019

Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication.

Ankur Mallick, Malhar Chaudhari, Utsav Sheth, Ganesh Palanikumar, Gauri Joshi

Proc. ACM Meas. Anal. Comput. Syst., 2019

Deep Probabilistic Kernels for Sample-Efficient Learning.

Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, Thomas Yong-Jin Han

CoRR, 2019

Rateless Codes for Distributed Computations with Sparse Compressed Matrices.

Ankur Mallick, Gauri Joshi

Proceedings of the IEEE International Symposium on Information Theory, 2019

Fast and Efficient Distributed Matrix-vector Multiplication Using Rateless Fountain Codes.

Ankur Mallick, Malhar Chaudhari, Gauri Joshi

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication.

Ankur Mallick, Malhar Chaudhari, Gauri Joshi

CoRR, 2018

2016

Bandlimited Field Reconstruction from Samples Obtained at Unknown Random Locations on a Grid.

Ankur Mallick, Animesh Kumar

CoRR, 2016

Bandlimited field reconstruction from samples obtained on a discrete grid with unknown random locations.

Ankur Mallick, Animesh Kumar

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016