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ORCIDBhanukiran Vinzamuri
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2020 – today
- 2024
[i7]Zhiqi Bu, Xiaomeng Jin, Bhanukiran Vinzamuri, Anil Ramakrishna, Kai-Wei Chang, Volkan Cevher, Mingyi Hong:
Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate. CoRR abs/2410.22086 (2024)- 2023
- [c19]Xiaomeng Jin, Bhanukiran Vinzamuri, Sriram Venkatapathy, Heng Ji, Pradeep Natarajan:
Adversarial Robustness for Large Language NER models using Disentanglement and Word Attributions. EMNLP (Findings) 2023: 12437-12450 - 2021
- [c18]Gowthami Somepalli, Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi:
Unsupervised anomaly detection with adversarial mirrored autoencoders. UAI 2021: 365-375 - [i6]Akshita Jha, Bhanukiran Vinzamuri, Chandan K. Reddy:
Fair Representation Learning using Interpolation Enabled Disentanglement. CoRR abs/2108.00295 (2021) - 2020
- [c17]Bhanukiran Vinzamuri, Elham Khabiri, Anuradha Bhamidipaty, Gregory Mckim, Biren Gandhi:
An End-to-End Context Aware Anomaly Detection System. IEEE BigData 2020: 1689-1698 - [c16]Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney:
Interpretable subgroup discovery in treatment effect estimation with application to opioid prescribing guidelines. CHIL 2020: 19-29 - [c15]Karthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang, Amit Dhurandhar:
Model Agnostic Multilevel Explanations. NeurIPS 2020 - [c14]Bhanukiran Vinzamuri, Elham Khabiri, Anuradha Bhamidipaty:
An Unsupervised Framework for Semantics Driven Causal Explanations for Anomalies. ISWC (Demos/Industry) 2020: 390-392 - [i5]Karthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang, Amit Dhurandhar:
Model Agnostic Multilevel Explanations. CoRR abs/2003.06005 (2020) - [i4]Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi:
Mirrored Autoencoders with Simplex Interpolation for Unsupervised Anomaly Detection. CoRR abs/2003.10713 (2020)
2010 – 2019
- 2019
- [c13]Elham Khabiri, Wesley M. Gifford, Bhanukiran Vinzamuri, Dhaval Patel, Pietro Mazzoleni:
Industry Specific Word Embedding and its Application in Log Classification. CIKM 2019: 2713-2721 - [i3]Chirag Nagpal, Dennis Wei, Bhanukiran Vinzamuri, Monica Shekhar, Sara E. Berger, Subhro Das, Kush R. Varshney:
Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines. CoRR abs/1905.03297 (2019) - 2018
- [j3]Flávio du Pin Calmon
, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Data Pre-Processing for Discrimination Prevention: Information-Theoretic Optimization and Analysis. IEEE J. Sel. Top. Signal Process. 12(5): 1106-1119 (2018) - [c12]Bhanukiran Vinzamuri, Kush R. Varshney:
False Discovery Rate Control with Concave Penalties Using Stability Selection. DSW 2018: 76-80 - [c11]Pin-Yu Chen, Bhanukiran Vinzamuri, Sijia Liu:
Is Ordered Weighted ℓ1 Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR. GlobalSIP 2018: 1174-1178 - [i2]Bernat Guillen Pegueroles, Bhanukiran Vinzamuri, Karthikeyan Shanmugam, Steve Hedden, Jonathan D. Moyer, Kush R. Varshney:
Structure Learning from Time Series with False Discovery Control. CoRR abs/1805.09909 (2018) - [i1]Pin-Yu Chen, Bhanukiran Vinzamuri, Sijia Liu:
Is Ordered Weighted ℓ1 Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR. CoRR abs/1809.08706 (2018) - 2017
- [j2]Bhanukiran Vinzamuri, Yan Li, Chandan K. Reddy:
Pre-Processing Censored Survival Data Using Inverse Covariance Matrix Based Calibration. IEEE Trans. Knowl. Data Eng. 29(10): 2111-2124 (2017) - [c10]Flávio P. Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, Kush R. Varshney:
Optimized Pre-Processing for Discrimination Prevention. NIPS 2017: 3992-4001 - 2016
- [c9]Ping Wang, Karthik K. Padthe, Bhanukiran Vinzamuri, Chandan K. Reddy:
CRISP: Consensus Regularized Selection based Prediction. CIKM 2016: 1019-1028 - [c8]Bhanukiran Vinzamuri, Karthik K. Padthe, Chandan K. Reddy:
Feature Grouping Using Weighted l1 Norm for High-Dimensional Data. ICDM 2016: 1233-1238 - [c7]Yan Li, Bhanukiran Vinzamuri, Chandan K. Reddy:
Regularized Weighted Linear Regression for High-dimensional Censored Data. SDM 2016: 45-53 - 2015
- [j1]Yan Li, Bhanukiran Vinzamuri, Chandan K. Reddy:
Constrained elastic net based knowledge transfer for healthcare information exchange. Data Min. Knowl. Discov. 29(4): 1094-1112 (2015) - 2014
- [c6]Bhanukiran Vinzamuri, Yan Li, Chandan K. Reddy:
Active Learning based Survival Regression for Censored Data. CIKM 2014: 241-250 - [c5]Vineeth Rakesh, Dilpreet Singh, Bhanukiran Vinzamuri, Chandan K. Reddy:
Personalized Recommendation of Twitter Lists using Content and Network Information. ICWSM 2014 - 2013
- [c4]Bhanukiran Vinzamuri, Chandan K. Reddy:
Cox Regression with Correlation Based Regularization for Electronic Health Records. ICDM 2013: 757-766 - [p1]Chandan K. Reddy, Bhanukiran Vinzamuri:
A Survey of Partitional and Hierarchical Clustering Algorithms. Data Clustering: Algorithms and Applications 2013: 87-110 - 2011
- [c3]Bhanukiran Vinzamuri, Kamalakar Karlapalem:
Designing an ensemble classifier over subspace classifiers using iterative convergence routine. CIKM 2011: 693-698 - [c2]Gaurav Maheshwari, Bhanukiran Vinzamuri, Vikram Pudi:
RNN Based Sampling Technique for Effective Active Learning. MLDM Posters 2011: 59-65 - 2010
- [c1]Bhanukiran Vinzamuri, Vikram Pudi:
A Robust Active Learning Framework Using Itemset Based Dynamic Rule Sampling. COMAD 2010: 103
Coauthor Index
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