14 citations · 26 across the 7 of their papers we have counts for
8 papers
ForensiBlock: A Provenance-Driven Blockchain Framework for Data Forensics and Auditability
Asma Jodeiri Akbarfam, Mahdieh Heidaripour, Hoda Maleki +2
Maintaining accurate provenance records is paramount in digital forensics, as they underpin evidence credibility and integrity, addressing essential aspects like accountability and…
Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning
Xiang Li, Dong Li, Ruoming Jin +2
Web-based interactions can be frequently represented by an attributed graph, and node clustering in such graphs has received much attention lately. Multiple efforts have successful…
DNNFusion: Accelerating Deep Neural Networks Execution with Advanced Operator Fusion
Wei Niu, Jiexiong Guan, Yanzhi Wang +2
Deep Neural Networks (DNNs) have emerged as the core enabler of many major applications on mobile devices. To achieve high accuracy, DNN models have become increasingly deep with h…
Adaptive Periodic Averaging: A Practical Approach to Reducing Communication in Distributed Learning
Peng Jiang, Gagan Agrawal
Stochastic Gradient Descent (SGD) is the key learning algorithm for many machine learning tasks. Because of its computational costs, there is a growing interest in accelerating SGD…
Towards Successful Social Media Advertising: Predicting the Influence of Commercial Tweets
Renhao Cui, Gagan Agrawal, Rajiv Ramnath
Businesses communicate using Twitter for a variety of reasons -- to raise awareness of their brands, to market new products, to respond to community comments, and to connect with t…
Tweets Can Tell: Activity Recognition using Hybrid Long Short-Term Memory Model
Renhao Cui, Gagan Agrawal, Rajiv Ramnath
This paper presents techniques to detect the "offline" activity a person is engaged in when she is tweeting (such as dining, shopping or entertainment), in order to create a dynami…
Pruned Landmark Labeling Meets Vertex Centric Computation: A Surprisingly Happy Marriage!
Ruoming Jin, Zhen Peng, Wendell Wu +3
In this paper, we study how the Pruned Landmark Labeling (PPL) algorithm can be parallelized in a scalable fashion, producing the same results as the sequential algorithm. More spe…
Fault Tolerant Frequent Pattern Mining
Sameh Shohdy, Abhinav Vishnu, Gagan Agrawal
FP-Growth algorithm is a Frequent Pattern Min- ing (FPM) algorithm that has been extensively used to study correlations and patterns in large scale datasets. While several research…