Prasanna Sattigeri
Prasanna Sattigeri
IBM Research AI, MIT-IBM Watson AI Lab
Verified email at us.ibm.com - Homepage
Title
Cited by
Cited by
Year
AI Fairness 360: An extensible toolkit for detecting, understanding, and mitigating unwanted algorithmic bias
RKE Bellamy, K Dey, M Hind, SC Hoffman, S Houde, K Kannan, P Lohia, ...
arXiv preprint arXiv:1810.01943, 2018
411*2018
Variational inference of disentangled latent concepts from unlabeled observations
A Kumar, P Sattigeri, A Balakrishnan
International Conference on Learning Representations (ICLR), 2018
2452018
Semi-supervised learning with gans: Manifold invariance with improved inference
A Kumar, P Sattigeri, T Fletcher
Advances in Neural Information Processing Systems 30, 2017
151*2017
One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques
V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ...
arXiv preprint arXiv:1909.03012, 2019
1262019
Co-regularized alignment for unsupervised domain adaptation
A Kumar, P Sattigeri, K Wadhawan, L Karlinsky, R Feris, WT Freeman, ...
arXiv preprint arXiv:1811.05443, 2018
892018
Fairness GAN: Generating datasets with fairness properties using a generative adversarial network
P Sattigeri, SC Hoffman, V Chenthamarakshan, KR Varshney
IBM Journal of Research and Development 63 (4/5), 3: 1-3: 9, 2019
73*2019
Optimizing kernel machines using deep learning
H Song, JJ Thiagarajan, P Sattigeri, A Spanias
IEEE transactions on neural networks and learning systems 29 (11), 5528-5540, 2018
472018
Understanding unequal gender classification accuracy from face images
V Muthukumar, T Pedapati, N Ratha, P Sattigeri, CW Wu, B Kingsbury, ...
arXiv preprint arXiv:1812.00099, 2018
35*2018
Quantitative resolution of nanoparticle sizes using single particle inductively coupled plasma mass spectrometry with the K-means clustering algorithm
X Bi, S Lee, JF Ranville, P Sattigeri, A Spanias, P Herckes, P Westerhoff
Journal of Analytical Atomic Spectrometry 29 (9), 1630-1639, 2014
332014
Ar-net: Adaptive frame resolution for efficient action recognition
Y Meng, CC Lin, R Panda, P Sattigeri, L Karlinsky, A Oliva, K Saenko, ...
European Conference on Computer Vision, 86-104, 2020
322020
Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions
P Sattigeri, KN Ramamurthy, JJ Thiagarajan, B Kailkhura
2020 54th Asilomar Conference on Signals, Systems, and Computers, 284-288, 2020
28*2020
Leveraging latent features for local explanations
R Luss, PY Chen, A Dhurandhar, P Sattigeri, Y Zhang, K Shanmugam, ...
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
27*2021
Electronic-nose for detecting environmental pollutants: Signal processing and analog front-end design
H Kim, B Konnanath, P Sattigeri, J Wang, A Mulchandani, N Myung, ...
Analog Integrated Circuits and Signal Processing 70 (1), 15-32, 2012
262012
Fairness of classifiers across skin tones in dermatology
NM Kinyanjui, T Odonga, C Cintas, NCF Codella, R Panda, P Sattigeri, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2020
25*2020
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.(2019)
V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ...
arXiv preprint arXiv:1909.03012, 1909
221909
How to foster innovation: A data-driven approach to measuring economic competitiveness
C Kuhlman, KN Ramamurthy, P Sattigeri, AC Lozano, L Cao, C Reddy, ...
IBM Journal of Research and Development 61 (6), 11: 1-11: 12, 2017
202017
A deep learning approach to multiple kernel fusion
H Song, JJ Thiagarajan, P Sattigeri, KN Ramamurthy, A Spanias
2017 IEEE international conference on acoustics, speech and signal …, 2017
202017
SUPERVISED LOCAL SPARSE CODING OF SUB-IMAGE FEATURES FOR IMAGE RETRIEVAL
JJ Thiagarajan, KN Ramamurthy, P Sattigeri, A Spanias
ICIP 2012, 2012
192012
Tafssl: Task-adaptive feature sub-space learning for few-shot classification
M Lichtenstein, P Sattigeri, R Feris, R Giryes, L Karlinsky
European Conference on Computer Vision, 522-539, 2020
182020
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models.
V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ...
J. Mach. Learn. Res. 21 (130), 1-6, 2020
182020
The system can't perform the operation now. Try again later.
Articles 1–20