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Vishnu Unnikrishnan 0002
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- affiliation: Otto-von-Guericke University Magdeburg, Knowledge Management & Discovery Lab, Germany
Other persons with the same name
- Vishnu Unnikrishnan 0001
— Tampere University, Finland (and 3 more)
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2020 – today
- 2024
- [b1]Vishnu Unnikrishnan:
Entity-centric machine learning: leveraging entity neighbourhoods for personalised predictors. Otto-von-Guericke University Magdeburg, Germany, 2024 - [i1]Vishnu Unnikrishnan, Clara Puga, Miro Schleicher, Uli Niemann, Berthold Langguth, Stefan Schoisswohl, Birgit Mazurek, Rilana Cima, Jose Antonio Lopez-Escamez, Dimitrios Kikidis, Eleftheria Vellidou, Rüdiger Pryss, Winfried Schlee, Myra Spiliopoulou:
Training and Validating a Treatment Recommender with Partial Verification Evidence. CoRR abs/2406.06654 (2024) - 2023
- [j5]Miro Schleicher
Prediction meets time series with gaps: User clusters with specific usage behavior patterns. Artif. Intell. Medicine 142: 102575 (2023) - [c14]Anna Kleinau, Simon Flügel, Rüdiger Pryss, Carsten Vogel, Milena Engelke, Winfried Schlee, Vishnu Unnikrishnan, Myra Spiliopoulou:
Predicting Patient-Based Time-Dependent Mobile Health Data. CBMS 2023: 79-84 - [c13]Vishnu Unnikrishnan
A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data. IDA 2023: 459-471 - 2022
- [c12]Noor Jamaludeen, Vishnu Unnikrishnan, André Brechmann, Myra Spiliopoulou:
Discovering Instantaneous Granger Causalities in Non-stationary Categorical Time Series Data. AIME 2022: 200-209 - 2021
- [j4]Subash Prakash, Vishnu Unnikrishnan
Interactive System for Similarity-Based Inspection and Assessment of the Well-Being of mHealth Users. Entropy 23(12): 1695 (2021) - [c11]Vishnu Unnikrishnan, Yash Shah, Miro Schleicher, Carlos Fernández-Viadero, Mirela Strandzheva, Doroteya Velikova, Plamen Dimitrov, Rüdiger Pryss, Johannes Schobel, Winfried Schlee, Myra Spiliopoulou:
Love thy Neighbours: A Framework for Error-Driven Discovery of Useful Neighbourhoods for One-Step Forecasts on EMA data. CBMS 2021: 295-300 - [c10]Saijal Shahania, Vishnu Unnikrishnan, Rüdiger Pryss, Robin Kraft
User-centric vs whole-stream learning for EMA prediction. CBMS 2021: 307-312 - [c9]Noor Jamaludeen
Circadian Conditional Granger Causalities on Ecological Momentary Assessment Data from an mHealth App. CBMS 2021: 354-359 - [c8]Clara Puga
Discovery of Patient Phenotypes through Multi-layer Network Analysis on the Example of Tinnitus. DSAA 2021: 1-10 - 2020
- [j3]Christian Beyer
Resource management for model learning at entity level. Ann. des Télécommunications 75(9-10): 549-561 (2020) - [j2]Christian Beyer
Active feature acquisition on data streams under feature drift. Ann. des Télécommunications 75(9-10): 597-611 (2020) - [j1]Vishnu Unnikrishnan
Entity-level stream classification: exploiting entity similarity to label the future observations referring to an entity. Int. J. Data Sci. Anal. 9(1): 1-15 (2020) - [c7]Vishnu Unnikrishnan, Yash Shah, Miro Schleicher, Mirela Strandzheva, Plamen Dimitrov, Doroteya Velikova, Rüdiger Pryss
Predicting the Health Condition of mHealth App Users with Large Differences in the Number of Recorded Observations - Where to Learn from? DS 2020: 659-673 - [c6]Abdullah Al Safi, Christian Beyer, Vishnu Unnikrishnan, Myra Spiliopoulou:
Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder. IDA 2020: 1-13 - [c5]Neetha Jambigi, Tirtha Chanda, Vishnu Unnikrishnan, Myra Spiliopoulou:
Assessing the Difficulty of Labelling an Instance in Crowdworking. PKDD/ECML Workshops 2020: 363-373
2010 – 2019
- 2019
- [c4]Noor Jamaludeen, Vishnu Unnikrishnan, Maya S. Sekeran, Majed Ali, Le Anh Trang, Myra Spiliopoulou:
Assessing the Reliability of Crowdsourced Labels via Twitter. LWDA 2019: 115-126 - [c3]Christian Beyer, Vishnu Unnikrishnan, Uli Niemann, Pawel Matuszyk, Eirini Ntoutsi, Myra Spiliopoulou:
Exploiting entity information for stream classification over a stream of reviews. SAC 2019: 564-573 - 2018
- [c2]Christian Beyer, Vishnu Unnikrishnan, Pawel Matuszyk, Uli Niemann, Rüdiger Pryss
Entity-Level Stream Classification: Exploiting Entity Similarity to Label the Future Observations Referring to an Entity. DSAA 2018: 246-255 - [c1]Christian Beyer, Uli Niemann
Predicting polarities of entity-centered documents without reading their contents. SAC 2018: 525-528
Coauthor Index
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last updated on 2024-10-21 21:26 CEST by the dblp team
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