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Pradeep Shenoy
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2020 – today
- 2024
- [c32]Nishant Jain, Pradeep Shenoy:
Instance-Conditional Timescales of Decay for Non-Stationary Learning. AAAI 2024: 12773-12781 - [c31]Soumyabrata Pal, Prateek Varshney, Gagan Madan, Prateek Jain, Abhradeep Thakurta, Gaurav Aggarwal, Pradeep Shenoy, Gaurav Srivastava:
Sample-Efficient Personalization: Modeling User Parameters as Low Rank Plus Sparse Components. AISTATS 2024: 1702-1710 - [c30]Nishant Jain, Arun S. Suggala, Pradeep Shenoy:
Improving Generalization via Meta-Learning on Hard Samples. CVPR 2024: 27590-27599 - [c29]Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy:
Learning model uncertainty as variance-minimizing instance weights. ICLR 2024 - [c28]Rishabh Tiwari, Durga Sivasubramanian, Anmol Reddy Mekala, Ganesh Ramakrishnan, Pradeep Shenoy:
Using Early Readouts to Mediate Featural Bias in Distillation. WACV 2024: 2626-2635 - [i19]Nishant Jain, Arun S. Suggala, Pradeep Shenoy:
Improving Generalization via Meta-Learning on Hard Samples. CoRR abs/2403.12236 (2024) - 2023
- [c27]Kushal Chauhan, Rishabh Tiwari, Jan Freyberg, Pradeep Shenoy, Krishnamurthy Dvijotham:
Interactive Concept Bottleneck Models. AAAI 2023: 5948-5955 - [c26]Durga Sivasubramanian, Ayush Maheshwari, Prathosh AP, Pradeep Shenoy, Ganesh Ramakrishnan:
Adaptive Mixing of Auxiliary Losses in Supervised Learning. AAAI 2023: 9855-9863 - [c25]Kushal Chauhan, Soumya Chatterjee, Akash Reddy, Aniruddha S, Balaraman Ravindran, Pradeep Shenoy:
Matching Options to Tasks using Option-Indexed Hierarchical Reinforcement Learning. AAMAS 2023: 2631-2633 - [c24]Aditay Tripathi, Rishubh Singh, Anirban Chakraborty, Pradeep Shenoy:
Edges to Shapes to Concepts: Adversarial Augmentation for Robust Vision. CVPR 2023: 24470-24479 - [c23]Rishabh Tiwari, Pradeep Shenoy:
Overcoming Simplicity Bias in Deep Networks using a Feature Sieve. ICML 2023: 34330-34343 - [c22]Barath Mohan Umapathi, Kushal Chauhan, Pradeep Shenoy, Devarajan Sridharan:
Shaken, and Stirred: Long-Range Dependencies Enable Robust Outlier Detection with PixelCNN++. IJCAI 2023: 1440-1450 - [i18]Rishabh Tiwari, Pradeep Shenoy:
Sifer: Overcoming simplicity bias in deep networks using a feature sieve. CoRR abs/2301.13293 (2023) - [i17]Nathan Beck, Suraj Kothawade, Pradeep Shenoy, Rishabh K. Iyer:
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings. CoRR abs/2305.10643 (2023) - [i16]Rishabh Tiwari, Durga Sivasubramanian, Anmol Reddy Mekala, Ganesh Ramakrishnan, Pradeep Shenoy:
Using Early Readouts to Mediate Featural Bias in Distillation. CoRR abs/2310.18590 (2023) - [i15]Anuj Srivastava, Karm Patel, Pradeep Shenoy, Devarajan Sridharan:
Rescuing referral failures during automated diagnosis of domain-shifted medical images. CoRR abs/2311.16766 (2023) - 2022
- [c21]Soumya Chatterjee, Aakriti Kumar, Pradeep Shenoy:
Meta-Learning of Dynamic Policy Adjustments in Inhibitory Control Tasks. CogSci 2022 - [c20]Rishabh Tiwari, KrishnaTeja Killamsetty, Rishabh K. Iyer, Pradeep Shenoy:
GCR: Gradient Coreset based Replay Buffer Selection for Continual Learning. CVPR 2022: 99-108 - [c19]Rishubh Singh, Pranav Gupta, Pradeep Shenoy, Ravikiran Sarvadevabhatla:
FLOAT: Factorized Learning of Object Attributes for Improved Multi-object Multi-part Scene Parsing. CVPR 2022: 1435-1445 - [c18]Kushal Chauhan, Barath Mohan Umapathi, Pradeep Shenoy, Manish Gupta, Devarajan Sridharan:
Robust outlier detection by de-biasing VAE likelihoods. CVPR 2022: 9871-9880 - [i14]Durga Sivasubramanian, Pradeep Shenoy, Prathosh AP, Ganesh Ramakrishnan:
ALM-KD: Knowledge Distillation with noisy labels via adaptive loss mixing. CoRR abs/2202.03250 (2022) - [i13]Rishubh Singh, Pranav Gupta, Pradeep Shenoy, Ravikiran Sarvadevabhatla:
FLOAT: Factorized Learning of Object Attributes for Improved Multi-object Multi-part Scene Parsing. CoRR abs/2203.16168 (2022) - [i12]Kushal Chauhan, Soumya Chatterjee, Akash Reddy, Balaraman Ravindran, Pradeep Shenoy:
Matching options to tasks using Option-Indexed Hierarchical Reinforcement Learning. CoRR abs/2206.05750 (2022) - [i11]Barath Mohan Umapathi, Kushal Chauhan, Pradeep Shenoy, Devarajan Sridharan:
Shaken, and Stirred: Long-Range Dependencies Enable Robust Outlier Detection with PixelCNN++. CoRR abs/2208.13579 (2022) - [i10]Soumyabrata Pal, Prateek Varshney, Prateek Jain, Abhradeep Guha Thakurta, Gagan Madan, Gaurav Aggarwal, Pradeep Shenoy, Gaurav Srivastava:
Private and Efficient Meta-Learning with Low Rank and Sparse Decomposition. CoRR abs/2210.03505 (2022) - [i9]Aditay Tripathi, Rishubh Singh, Anirban Chakraborty, Pradeep Shenoy:
Robustifying Deep Vision Models Through Shape Sensitization. CoRR abs/2211.07277 (2022) - [i8]Nishant Jain, Pradeep Shenoy:
Learning on non-stationary data with re-weighting. CoRR abs/2212.05908 (2022) - [i7]Nishant Jain, Pradeep Shenoy:
Selective classification using a robust meta-learning approach. CoRR abs/2212.05987 (2022) - [i6]Kushal Chauhan, Rishabh Tiwari, Jan Freyberg, Pradeep Shenoy, Krishnamurthy Dvijotham:
Interactive Concept Bottleneck Models. CoRR abs/2212.07430 (2022) - 2021
- [c17]Soumya Chatterjee, Pradeep Shenoy:
Model-Agnostic Fits for Understanding Information Seeking Patterns in Humans. AAAI 2021: 784-791 - [c16]Vishwajeet Agrawal, Pradeep Shenoy:
Tracking what matters: A decision-variable account of human behavior in bandit tasks. CogSci 2021 - [i5]Ananye Agarwal, Pradeep Shenoy, Mausam:
End-to-End Neuro-Symbolic Architecture for Image-to-Image Reasoning Tasks. CoRR abs/2106.03121 (2021) - [i4]Kushal Chauhan, Pradeep Shenoy, Manish Gupta, Devarajan Sridharan:
Efficient remedies for outlier detection with variational autoencoders. CoRR abs/2108.08760 (2021) - [i3]Rishabh Tiwari, KrishnaTeja Killamsetty, Rishabh K. Iyer, Pradeep Shenoy:
GCR: Gradient Coreset Based Replay Buffer Selection For Continual Learning. CoRR abs/2111.11210 (2021) - 2020
- [i2]Soumya Chatterjee, Pradeep Shenoy:
Model-agnostic Fits for Understanding Information Seeking Patterns in Humans. CoRR abs/2012.04858 (2020)
2010 – 2019
- 2013
- [c15]Pradeep Shenoy, Angela J. Yu:
Rational preference shifts in multi-attribute choice: what is fair? CogSci 2013 - 2012
- [c14]Pradeep Shenoy, Angela J. Yu:
Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making. NIPS 2012: 2132-2140 - 2010
- [c13]Pradeep Shenoy, Rajesh P. N. Rao, Angela J. Yu:
A rational decision making framework for inhibitory control. NIPS 2010: 2146-2154
2000 – 2009
- 2008
- [j4]Pradeep Shenoy, Kai J. Miller, Jeffrey G. Ojemann, Rajesh P. N. Rao:
Generalized Features for Electrocorticographic BCIs. IEEE Trans. Biomed. Eng. 55(1): 273-280 (2008) - [j3]Pradeep Shenoy, Kai J. Miller, Beau Crawford, Rajesh P. N. Rao:
Online Electromyographic Control of a Robotic Prosthesis. IEEE Trans. Biomed. Eng. 55(3): 1128-1135 (2008) - [j2]Kai J. Miller, Pradeep Shenoy, Marcel den Nijs, Larry B. Sorensen, Rajesh P. N. Rao, Jeffrey G. Ojemann:
Beyond the Gamma Band: The Role of High-Frequency Features in Movement Classification. IEEE Trans. Biomed. Eng. 55(5): 1634-1637 (2008) - [c12]David B. Grimes, Desney S. Tan, Scott E. Hudson, Pradeep Shenoy, Rajesh P. N. Rao:
Feasibility and pragmatics of classifying working memory load with an electroencephalograph. CHI 2008: 835-844 - [c11]Pradeep Shenoy, Desney S. Tan:
Human-aided computing: utilizing implicit human processing to classify images. CHI 2008: 845-854 - [c10]Ashish Kapoor, Pradeep Shenoy, Desney S. Tan:
Combining brain computer interfaces with vision for object categorization. CVPR 2008 - [c9]Ashish Kapoor, Desney S. Tan, Pradeep Shenoy, Eric Horvitz:
Complementary computing for visual tasks: Meshing computer vision with human visual processing. FG 2008: 1-7 - 2007
- [j1]Kai J. Miller, Marcel den Nijs, Pradeep Shenoy, John W. Miller, Rajesh P. N. Rao, Jeffrey G. Ojemann:
Real-time functional brain mapping using electrocorticography. NeuroImage 37(2): 504-507 (2007) - 2005
- [c8]Beau Crawford, Kai J. Miller, Pradeep Shenoy, Rajesh P. N. Rao:
Real-Time Classification of Electromyographic Signals for Robotic Control. AAAI 2005: 523-528 - 2004
- [c7]Pradeep Shenoy, Rajesh P. N. Rao:
Dynamic Bayesian Networks for Brain-Computer Interfaces. NIPS 2004: 1265-1272 - 2003
- [c6]Jayant Madhavan, Philip A. Bernstein, Kuang Chen, Alon Y. Halevy, Pradeep Shenoy:
Corpus-based Schema Matching. IIWeb 2003: 59-63 - [c5]Philip Bohannon, Xin Dong, Sumit Ganguly, Henry F. Korth, Chengkai Li, P. P. S. Narayan, Pradeep Shenoy:
ROLEX: Relational On-Line Exchange with XML. SIGMOD Conference 2003: 673 - 2002
- [c4]Raghav Kaushik, Pradeep Shenoy, Philip Bohannon, Ehud Gudes:
Exploiting Local Similarity for Indexing Paths in Graph-Structured Data. ICDE 2002: 129-140 - [c3]Philip Bohannon, Sumit Ganguly, Henry F. Korth, P. P. S. Narayan, Pradeep Shenoy:
Optimizing View Queries in ROLEX to Support Navigable Result Trees. VLDB 2002: 119-130 - [c2]Raghav Kaushik, Philip Bohannon, Jeffrey F. Naughton, Pradeep Shenoy:
Updates for Structure Indexes. VLDB 2002: 239-250 - 2000
- [c1]Pradeep Shenoy, Jayant R. Haritsa, S. Sudarshan, Gaurav Bhalotia, Mayank Bawa, Devavrat Shah:
Turbo-charging Vertical Mining of Large Databases. SIGMOD Conference 2000: 22-33 - [i1]Prasan Roy, Krithi Ramamritham, S. Seshadri, Pradeep Shenoy, S. Sudarshan:
Don't Trash your Intermediate Results, Cache 'em. CoRR cs.DB/0003005 (2000)
Coauthor Index
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last updated on 2024-10-08 21:27 CEST by the dblp team
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