E-LIB Suche - Ergebnisse für: Ramanan, Nandini

1

Relational Active Feature Elicitation for DDDAS:

, In: Lecture Notes in Computer Science; Dynamic Data Driven Applications Systems,

Ramanan, Nandini ; Odom, Phillip ; Blasch, Erik.. - p. 227-232 , 2024

2

Active Feature Acquisition via Human Interaction in Relatio..:

, In: Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD),

Ramanan, Nandini ; Odom, Phillip ; Kersting, Kristian. - p. 70-78 , 2023

Link: https://dl.acm.org/doi/1..

3

Active feature elicitation: An unified framework:

Das, Srijita ; Ramanan, Nandini ; Kunapuli, Gautam..
Frontiers in Artificial Intelligence. 6 (2023) - p. , 2023

Link: https://doi.org/10.3389/..

4

Boosted Embeddings for Time-Series Forecasting:

, In: Machine Learning, Optimization, and Data Science; Lecture Notes in Computer Science,

Karingula, Sankeerth Rao ; Ramanan, Nandini ; Tahmasbi, Rasool... - p. 1-14 , 2022

Link: https://doi.org/10.1007/..

5

Structure learning for relational logistic regression: an e..:

Ramanan, Nandini ; Kunapuli, Gautam ; Khot, Tushar...
Data Mining and Knowledge Discovery. 35 (2021) 5 - p. 2089-2111 , 2021

Link: https://doi.org/10.1007/..

6

Interactive Transfer Learning in Relational Domains:

Kumaraswamy, Raksha ; Ramanan, Nandini ; Odom, Phillip.
KI - Künstliche Intelligenz. 34 (2020) 2 - p. 181-192 , 2020

Link: https://doi.org/10.1007/..

7

Few-Shot Induction of Generalized Logical Concepts via Huma..:

Das, Mayukh ; Ramanan, Nandini ; Doppa, Janardhan Rao.
Frontiers in Robotics and AI. 7 (2020) - p. , 2020

Link: https://doi.org/10.3389/..

8

Causal Learning From Predictive Modeling for Observational ..:

Ramanan, Nandini ; Natarajan, Sriraam
Frontiers in Big Data. 3 (2020) - p. , 2020

Link: https://doi.org/10.3389/..

9

Boosting for postpartum depression prediction:

, In: Proceedings of the Second IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies,

Natarajan, Sriraam ; Prabhakar, Annu ; Ramanan, Nandini... - p. 232-240 , 2017

Link: https://dl.acm.org/doi/1..

10

Contrastive Credibility Propagation for Reliable Semi-Super..:

Kutt, Brody ; Ramteke, Pralay ; Mignot, Xavier...
http://arxiv.org/abs/2211.09929. , 2022

Link: http://arxiv.org/abs/221..

11

Time Series Anomaly Detection with label-free Model Selecti..:

Jung, Deokwoo ; Ramanan, Nandini ; Amjadi, Mehrnaz...
http://arxiv.org/abs/2106.07473. , 2021

Link: http://arxiv.org/abs/210..

12

Real-time Drift Detection on Time-series Data:

Ramanan, Nandini ; Tahmasbi, Rasool ; Sayer, Marjorie...
http://arxiv.org/abs/2110.06383. , 2021

Link: http://arxiv.org/abs/211..

13

Boosted Embeddings for Time Series Forecasting:

Karingula, Sankeerth Rao ; Ramanan, Nandini ; Tahmasbi, Rasool...
http://arxiv.org/abs/2104.04781. , 2021

Link: http://arxiv.org/abs/210..

14

Log2NS: Enhancing Deep Learning Based Analysis of Logs With..:

Thimmisetty, Charanraj ; Tiwari, Praveen ; de la Iglesia, Didac Gil...
http://arxiv.org/abs/2105.14149. , 2021

Link: http://arxiv.org/abs/210..

15

Causal Learning From Predictive Modeling for Observational ..:

Ramanan, Nandini ; Natarajan, Sriraam
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931928/. , 2020

Link: http://www.ncbi.nlm.nih...