1 citations · 2 across the 5 of their papers we have counts for
5 papers
LayoutBench: Performance Benchmarking of Cloud Storage Layouts for Multimedia Data
Debopam Sanyal, Hongjie Chen, Alexey Tumanov +1
Modern multimedia machine learning workloads increasingly store large-scale datasets in cloud object storage services such as AWS S3. How these samples are physically organized in…
Robust Federated Learning Under Real-World Client Churn
Dhruv Garg, Neha Lakhani, Debopam Sanyal +3
Federated Learning (FL) enables training shared models on private, on-device data, but production deployments remain constrained to slow, multi-day refresh cycles due to the comple…
KLAS: Using Similarity to Stitch Neural Networks for Improved Accuracy-Efficiency Tradeoffs
Debopam Sanyal, Anantharaman Iyer, Alind Khare +5
Given the wide range of deployment targets, flexible model selection is essential for optimizing performance within a given compute budget. Recent work demonstrates that stitching…
DPAR: Dynamic Patchification for Efficient Autoregressive Visual Generation
Divyansh Srivastava, Akshay Mehra, Pranav Maneriker +5
Decoder-only autoregressive image generation typically relies on fixed-length tokenization schemes whose token counts grow quadratically with resolution, substantially increasing t…
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems
Debopam Sanyal, Jui-Tse Hung, Manav Agrawal +6
Model-serving systems have become increasingly popular, especially in real-time web applications. In such systems, users send queries to the server and specify the desired performa…