Dr. Sahely Bhadra

Publications

2020 -

  1. CDGCN: Conditional de novo Drug Generative Model Using Graph Convolution Networks.
    Shikha Mallick, and Sahely Bhadra
    Research in Computational Molecular Biology - 27th Annual International Conference, {RECOMB} Lecture Notes in Computer Science, volume 13976, Pages 104-119link(2023)

  2. Warping resilient scalable anomaly detection in time series.
    S. Abilasha, Sahely Bhadra, P. Deepak and Anish Mathew
    Neurocomputing,Volume 511,Pages 22-33 link(2022)

  3. Deep Extreme Mixture Model for Time Series Forecasting.
    Abilasha S., Sahely Bhadra, Ahmed Zaheer Dadarkar and Deepak P.
    The 31st ACM International Conference on Information and Knowledge Management (CIKM ’22) (2022)

  4. Learning primal-dual sparse kernel machines.
    Riikka Huusari, Sahely Bhadra, Cécile Capponi, Hachem Kadri and Juho Rousu
    CoRR abs/2108.12199 (2021)

  5. Understanding the limitations of network online learning.
    Timothy LaRock, Timothy Sakharov, Sahely Bhadra, Tina Eliassi-Rad:
    Applied Network Science 5 (1) 60 (2020)

Before 2020

  1. Large-Scale Sparse Kernel Canonical Correlation Analysis
    Viivi Uurtio , Sahely Bhadra and Juho Rousu
    Proceedings of the 36th International Conference on Machine Learning(ICML) 6383–6391 (2019)

  2. Warping Resilient Time Series Embeddings
    Anish Mathew, Deepak P and Sahely Bhadra
    ICML 2019 Time Series Workshop (2019)

  3. Book Chapter: Multi-View Data Completion
    Sahely Bhadra
    P D., Jurek-Loughrey A. (eds) Linking and Mining Heterogeneous and Multi-view Data. Unsupervised and Semi-Supervised Learning. Springer, Cham 1-25 (2019)

  4. Sparse Non-Linear CCA through Hilbert-Schmidt Independence Criterion
    Viivi Uurtio, Sahely Bhadra, Juho Rusu
    IEEE International Conference on Data Mining (ICDM’18) (2018)

  5. Limits of Learning in Incomplete Networks
    Timothy Larock, Timothy Sakhrov, Sahely Bhadra and Tina Eliassi - Rad.
    International School and Conference of Network Science (NetSci) (2018)

  6. Reducing Network Incompleteness Through Online Learning: A Feasibility Study
    Timothy LaRock, Timothy Sakharov, Sahely Bhadra and Tina Eliassi-Rad
    Accepted for 14th International Workshop on Mining and Learning with Graphs (MLG) (2018)

  7. Book Chapter: Analysis of Fluxomic Experiments with Principal Metabolic Flux Mode Analysis
    Sahely Bhadra and Juho Rousu
    Springer Book : Data Mining for Systems Biology (2018)

  8. Principal Metabolic Flux Mode Analysis
    Sahely Bhadra, Peter Blomberg, Sandra Castillo, and Juho Rousu.
    Bioinformatics 34 (14) 2409–2417 (2018)

  9. Multi-view Kernel Completion.
    Sahely Bhadra, Samuel Kaski and Juho Rousu.
    Machine Learning 106 (5), 713-739, 2017

  10. Correction of Noisy Labels via Mutual Consistency Check.
    Sahely Bhadra, Matthias Hein.
    Neurocomputing (160): 34-52, 2015.

  11. Efficient Methods for Robust Classification Under Uncertainty in Kernel Matrices.
    Aharon Ben-Tal, Sahely Bhadra, Chiranjib Bhattacharyya and Arkadi Nemirovski.
    Journal of Machine Learning Research 13 (Oct):2923.2954, 2012.

  12. Web Information Extraction Using Markov Logic Networks (pdf).
    Sandeepkumar Satpal, Sahely Bhadra, S Sundararajan, Rajeev Rastogi, Prithviraj Sen.
    17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)2011.

  13. Web Information Extraction Using Markov Logic Networks (Poster).
    Sandeepkumar Satpal, Sahely Bhadra, S Sundararajan, Rajeev Rastogi, Prithviraj Sen.
    International World Wide Web Conferences (WWW) 2011.

  14. Chance constrained uncertain classification via robust optimization.
    Aharon Ben-Tal, Sahely Bhadra, Chiranjib Bhattacharyya and J. Saketha Nath.
    Mathematical Programming Series B, 2011.

  15. Robust Formulations for Handling Uncertainty in Kernel Matrices(paper,demo).
    Sahely Bhadra, Sourangshu Bhattacharrya , Chiranjib Bhattacharyya and Aharon Ben-Tal.
    International Conference on Machine Learning (ICML) 2010.

  16. Interval Data Classification under Partial Information: A Chance-Constraint Approach (pdf).
    Sahely Bhadra, J. Saketha Nath, Aharon Ben-Tal and Chiranjib Bhattacharyya.
    Achieved Best Runner-up certificate in PAKDD-2009.

  17. A Linear Programming Approach for Estimating the Structure of a Sparse Linear Genetic Network from Transcript Profiling Data.
    S. Bhadra , C. Bhattacharyya , N. Chandra , I.S. Mian.
    Accepted for Journal of Algorithms for Molecular Biology, 2009.