Shameem Puthiya Parambath

Orcid: 0000-0002-5338-9385

According to our database1, Shameem Puthiya Parambath authored at least 28 papers between 2012 and 2025.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
STaRFormer: Semi-Supervised Task-Informed Representation Learning via Dynamic Attention-Based Regional Masking for Sequential Data.
CoRR, April, 2025

Distributed Log-driven Anomaly Detection System based on Evolving Decision Making.
CoRR, April, 2025

Advanced Persistent Threats Based on Supply Chain Vulnerabilities: Challenges, Solutions, and Future Directions.
IEEE Internet Things J., March, 2025

Node selection using adversarial expert-based multi-armed bandits in distributed computing.
Computing, March, 2025

Thompson sampling-based recursive block elimination for dynamic assignment under limited budget in pure-exploration.
Data Min. Knowl. Discov., January, 2025

2024
Sequential query prediction based on multi-armed bandits with ensemble of transformer experts and immediate feedback.
Data Min. Knowl. Discov., November, 2024

Unified Semantic Log Parsing and Causal Graph Construction for Attack Attribution.
Dataset, November, 2024

Unified Semantic Log Parsing and Causal Graph Construction for Attack Attribution.
CoRR, 2024

The Price of Labelling: A Two-Phase Federated Self-learning Approach.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Sequential Block Elimination for Dynamic Pricing.
Proceedings of the IEEE International Conference on Data Mining, 2024

CL-FML: Cluster-Based & Label-Aware Federated Meta-Learning for On-Demand Classification Tasks.
Proceedings of the 11th IEEE International Conference on Data Science and Advanced Analytics, 2024

LIFE: Leader-driven Hierarchical & Inclusive Federated Learning.
Proceedings of the IEEE International Conference on Big Data, 2024

2023
FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental Regularization.
Proceedings of the IEEE International Conference on Data Mining, 2023

2022
Improving Sequential Query Recommendation with Immediate User Feedback.
CoRR, 2022

Parameter Tuning of Reranking-based Diversification Algorithms using Total Curvature Analysis.
Proceedings of the ICTIR '22: The 2022 ACM SIGIR International Conference on the Theory of Information Retrieval, Madrid, Spain, July 11, 2022

2021
Permutation-Invariant Subgraph Discovery.
CoRR, 2021

Max-Utility Based Arm Selection Strategy For Sequential Query Recommendations.
Proceedings of the Asian Conference on Machine Learning, 2021

2020
Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations.
Data Min. Knowl. Discov., 2020

Popularity Agnostic Evaluation of Knowledge Graph Embeddings.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019
Re-ranking Based Diversification: A Unifying View.
CoRR, 2019

Risk Aware Ranking for Top-k Recommendations.
CoRR, 2019

2018
Reuse and Adaptation for Entity Resolution through Transfer Learning.
CoRR, 2018

SAGA: A Submodular Greedy Algorithm for Group Recommendation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016
New methods for multi-objective learning. (Nouvelles méthodes pour l'apprentissage multi-objectifs).
PhD thesis, 2016

A Coverage-Based Approach to Recommendation Diversity On Similarity Graph.
Proceedings of the 10th ACM Conference on Recommender Systems, 2016

2015
Theory of Optimizing Pseudolinear Performance Measures: Application to F-measure.
CoRR, 2015

2014
Optimizing F-Measures by Cost-Sensitive Classification.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2012
Topic Extraction and Bundling of Related Scientific Articles
CoRR, 2012


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