110 citations · 168 across the 10 of their papers we have counts for
10 papers
BagPipe: Accelerating Deep Recommendation Model Training
Saurabh Agarwal, Chengpo Yan, Ziyi Zhang +1
Deep learning based recommendation models (DLRM) are widely used in several business critical applications. Training such recommendation models efficiently is challenging because t…
AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning
Yuhan Liu, Saurabh Agarwal, Shivaram Venkataraman
With the rapid adoption of machine learning (ML), a number of domains now use the approach of fine tuning models which were pre-trained on a large corpus of data. However, our expe…
Pufferfish: Communication-efficient Models At No Extra Cost
Hongyi Wang, Saurabh Agarwal, Dimitris Papailiopoulos
To mitigate communication overheads in distributed model training, several studies propose the use of compressed stochastic gradients, usually achieved by sparsification or quantiz…
On the Utility of Gradient Compression in Distributed Training Systems
Saurabh Agarwal, Hongyi Wang, Shivaram Venkataraman +1
A rich body of prior work has highlighted the existence of communication bottlenecks in synchronous data-parallel training. To alleviate these bottlenecks, a long line of recent wo…
Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification
Saurabh Agarwal, Hongyi Wang, Kangwook Lee +2
Distributed model training suffers from communication bottlenecks due to frequent model updates transmitted across compute nodes. To alleviate these bottlenecks, practitioners use…
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
Hongyi Wang, Kartik Sreenivasan, Shashank Rajput +5
Due to its decentralized nature, Federated Learning (FL) lends itself to adversarial attacks in the form of backdoors during training. The goal of a backdoor is to corrupt the perf…
Scalable K-Medoids via True Error Bound and Familywise Bandits
Aravindakshan Babu, Saurabh Agarwal, Sudarshan Babu +1
K-Medoids(KM) is a standard clustering method, used extensively on semi-metric data.Error analyses of KM have traditionally used an in-sample notion of error,which can be far from…
Graph based Question Answering System
Piyush Mital, Saurabh Agarwal, Bhargavi Neti +6
In today's digital age in the dawning era of big data analytics it is not the information but the linking of information through entities and actions which defines the discourse. A…
Framework for Application Mapping over Packet-Switched Network of FPGAs: Case Studies
Vinay B. Y. Kumar, Pinalkumar Engineer, Mandar Datar +4
The algorithm-to-hardware High-level synthesis (HLS) tools today are purported to produce hardware comparable in quality to handcrafted designs, particularly with user directive dr…
A Novel Approach to Develop a New Hybrid Technique for Trademark Image Retrieval
Saurabh Agarwal, Punit Kumar Johari
Trademark Image Retrieval is playing a vital role as a part of CBIR System. Trademark is of great significance because it carries the status value of any company. To retrieve such…