Atif Hassan

Orcid: 0000-0002-7795-756X

According to our database1, Atif Hassan authored at least 13 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
A Positive-Unlabeled Learning Approach With Self-Correcting Regularized Risk.
IEEE Trans. Artif. Intell., March, 2026

2025
Forecast2Anomaly (F2A): Adapting Multivariate Time Series Foundation Models for Anomaly Prediction.
CoRR, November, 2025

A wrapper feature selection approach using Markov blankets.
Pattern Recognit., 2025

The Counterfactual-Dialectical Optimization Framework: A Prescriptive Approach to Employee Attrition Management with Empirical Validation.
Inf., 2025

SALSA: A Secure, Adaptive and Label-Agnostic Scalable Algorithm for Machine Unlearning.
Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

SPvR: Structured Pruning via Ranking.
Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

RCAP: Robust, Class-Aware, Probabilistic Dynamic Dataset Pruning.
Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

2022
Evaluating the Robustness of Biomedical Concept Normalization.
Proceedings of the Transfer Learning for Natural Language Processing Workshop, 2022

Dynamic Forward and Backward Sparse Training (DFBST): Accelerated Deep Learning through Completely Sparse Training Schedule.
Proceedings of the Asian Conference on Machine Learning, 2022

2021
PPFS: Predictive Permutation Feature Selection.
CoRR, 2021

2020
An Ensemble-Learning Based Application to Predict the Earlier Stages of Alzheimer's Disease (AD).
IEEE Access, 2020

ERLKG: Entity Representation Learning and Knowledge Graph based association analysis of COVID-19 through mining of unstructured biomedical corpora.
Proceedings of the First Workshop on Scholarly Document Processing, 2020

2019
Cluster-Based Relative Outlier Under-Sampling Technique.
Proceedings of the Advances in Data Mining, 2019


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