193 citations · 319 across the 21 of their papers we have counts for
21 papers
Continuously Reliable Detection of New-Normal Misinformation: Semantic Masking and Contrastive Smoothing in High-Density Latent Regions
Abhijit Suprem, Joao Eduardo Ferreira, Calton Pu
Toxic misinformation campaigns have caused significant societal harm, e.g., affecting elections and COVID-19 information awareness. Unfortunately, despite successes of (gold standa…
Time-Aware Datasets are Adaptive Knowledgebases for the New Normal
Abhijit Suprem, Sanjyot Vaidya, Joao Eduardo Ferreira +1
Recent advances in text classification and knowledge capture in language models have relied on availability of large-scale text datasets. However, language models are trained on st…
ATEAM: Knowledge Integration from Federated Datasets for Vehicle Feature Extraction using Annotation Team of Experts
Abhijit Suprem, Purva Singh, Suma Cherkadi +3
The vehicle recognition area, including vehicle make-model recognition (VMMR), re-id, tracking, and parts-detection, has made significant progress in recent years, driven by severa…
EdnaML: A Declarative API and Framework for Reproducible Deep Learning
Abhijit Suprem, Sanjyot Vaidya, Avinash Venugopal +2
Machine Learning has become the bedrock of recent advances in text, image, video, and audio processing and generation. Most production systems deal with several models during deplo…
Evaluating Generalizability of Fine-Tuned Models for Fake News Detection
Abhijit Suprem, Calton Pu
The Covid-19 pandemic has caused a dramatic and parallel rise in dangerous misinformation, denoted an `infodemic' by the CDC and WHO. Misinformation tied to the Covid-19 infodemic…
Constructive Interpretability with CoLabel: Corroborative Integration, Complementary Features, and Collaborative Learning
Abhijit Suprem, Sanjyot Vaidya, Suma Cherkadi +3
Machine learning models with explainable predictions are increasingly sought after, especially for real-world, mission-critical applications that require bias detection and risk mi…
MiDAS: Multi-integrated Domain Adaptive Supervision for Fake News Detection
Abhijit Suprem, Calton Pu
COVID-19 related misinformation and fake news, coined an 'infodemic', has dramatically increased over the past few years. This misinformation exhibits concept drift, where the dist…
Challenges and Opportunities in Rapid Epidemic Information Propagation with Live Knowledge Aggregation from Social Media
Calton Pu, Abhijit Suprem, Rodrigo Alves Lima
A rapidly evolving situation such as the COVID-19 pandemic is a significant challenge for AI/ML models because of its unpredictability. %The most reliable indicator of the pandemic…
EDNA-Covid: A Large-Scale Covid-19 Tweets Dataset Collected with the EDNA Streaming Toolkit
Abhijit Suprem, Calton Pu
The Covid-19 pandemic has fundamentally altered many facets of our lives. With nationwide lockdowns and stay-at-home advisories, conversations about the pandemic have naturally mov…
ODIN: Automated Drift Detection and Recovery in Video Analytics
Abhijit Suprem, Joy Arulraj, Calton Pu +1
Recent advances in computer vision have led to a resurgence of interest in visual data analytics. Researchers are developing systems for effectively and efficiently analyzing visua…
Looking GLAMORous: Vehicle Re-Id in Heterogeneous Cameras Networks with Global and Local Attention
Abhijit Suprem, Calton Pu
Vehicle re-identification (re-id) is a fundamental problem for modern surveillance camera networks. Existing approaches for vehicle re-id utilize global features and local features…
Small, Accurate, and Fast Vehicle Re-ID on the Edge: the SAFR Approach
Abhijit Suprem, Calton Pu, Joao Eduardo Ferreira
We propose a Small, Accurate, and Fast Re-ID (SAFR) design for flexible vehicle re-id under a variety of compute environments such as cloud, mobile, edge, or embedded devices by on…
EventMapper: Detecting Real-World Physical Events Using Corroborative and Probabilistic Sources
Abhijit Suprem, Calton Pu
The ubiquity of social media makes it a rich source for physical event detection, such as disasters, and as a potential resource for crisis management resource allocation. There ha…
Robust, Extensible, and Fast: Teamed Classifiers for Vehicle Tracking and Vehicle Re-ID in Multi-Camera Networks
Abhijit Suprem, Rodrigo Alves Lima, Bruno Padilha +2
As camera networks have become more ubiquitous over the past decade, the research interest in video management has shifted to analytics on multi-camera networks. This includes perf…
Event Detection in Noisy Streaming Data with Combination of Corroborative and Probabilistic Sources
Abhijit Suprem, Calton Pu
Global physical event detection has traditionally relied on dense coverage of physical sensors around the world; while this is an expensive undertaking, there have not been alterna…
Concept Drift Adaptive Physical Event Detection for Social Media Streams
Abhijit Suprem, Aibek Musaev, Calton Pu
Event detection has long been the domain of physical sensors operating in a static dataset assumption. The prevalence of social media and web access has led to the emergence of soc…
ASSED -- A Framework for Identifying Physical Events through Adaptive Social Sensor Data Filtering
Abhijit Suprem, Calton Pu
Physical event detection has long been the domain of static event processors operating on numeric sensor data. This works well for large scale strong-signal events such as hurrican…
Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks
Yanzhao Wu, Ling Liu, Juhyun Bae +6
Learning Rate (LR) is an important hyper-parameter to tune for effective training of deep neural networks (DNNs). Even for the baseline of a constant learning rate, it is non-trivi…
Differentially Private Model Publishing for Deep Learning
Lei Yu, Ling Liu, Calton Pu +2
Deep learning techniques based on neural networks have shown significant success in a wide range of AI tasks. Large-scale training datasets are one of the critical factors for thei…
A Comparative Measurement Study of Deep Learning as a Service Framework
Yanzhao Wu, Ling Liu, Calton Pu +4
Big data powered Deep Learning (DL) and its applications have blossomed in recent years, fueled by three technological trends: a large amount of digitized data openly accessible, a…
A Comparative Study of Containers and Virtual Machines in Big Data Environment
Qi Zhang, Ling Liu, Calton Pu +3
Container technique is gaining increasing attention in recent years and has become an alternative to traditional virtual machines. Some of the primary motivations for the enterpris…