Shubhendu Trivedi

Affiliations:
  • Massachusetts Institute of Technology (MIT), Computer Science and Artificial Intelligence Laboratory (CSAIL), Cambridge, MA, USA
  • Brown University, Institute for Computational and Experimental Research in Mathematics (ICERM), Providence, RI, USA (former)
  • University of Chicago, IL, USA (former, PhD 2018)
  • Toyota Technological Institute at Chicago, IL, USA (former)
  • Worcester Polytechnic Institute, Department of Computer Science, MA, USA (former)


According to our database1, Shubhendu Trivedi authored at least 34 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

Legend:

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Links

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Bibliography

2024
Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models.
Trans. Mach. Learn. Res., 2024

Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks.
CoRR, 2024

Improving Equivariant Model Training via Constraint Relaxation.
CoRR, 2024

Position Paper: Generalized grammar rules and structure-based generalization beyond classical equivariance for lexical tasks and transduction.
CoRR, 2024

Contextualized Sequence Likelihood: Enhanced Confidence Scores for Natural Language Generation.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control.
Proceedings of the International Conference on Machine Learning, 2023

Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Conformal Prediction Intervals with Temporal Dependence.
Trans. Mach. Learn. Res., 2022

Conformal Prediction with Temporal Quantile Adjustments.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views?
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Locally Valid and Discriminative Confidence Intervals for Deep Learning Models.
CoRR, 2021

DeepSZ: Identification of Sunyaev-Zel'dovich Galaxy Clusters using Deep Learning.
CoRR, 2021

Locally Valid and Discriminative Prediction Intervals for Deep Learning Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Rotation-Invariant Autoencoders for Signals on Spheres.
CoRR, 2020

The Expected Jacobian Outerproduct: Theory and Empirics.
CoRR, 2020

2019
Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan".
CoRR, 2019

Asymmetric Multiresolution Matrix Factorization.
CoRR, 2019

Deep Learning for Automated Classification and Characterization of Amorphous Materials.
CoRR, 2019

DeepCMB: Lensing reconstruction of the cosmic microwave background with deep neural networks.
Astron. Comput., 2019

2018
Discriminative Learning of Similarity and Group Equivariant Representations.
CoRR, 2018

Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups.
Proceedings of the 35th International Conference on Machine Learning, 2018

Covariant Compositional Networks For Learning Graphs.
Proceedings of the 6th International Conference on Learning Representations, 2018

2015
The Utility of Clustering in Prediction Tasks.
CoRR, 2015

2014
A Consistent Estimator of the Expected Gradient Outerproduct.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Discriminative Metric Learning by Neighborhood Gerrymandering.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Applying Clustering to the Problem of Predicting Retention within an ITS: Comparing Regularity Clustering with Traditional Methods.
Proceedings of the Twenty-Sixth International Florida Artificial Intelligence Research Society Conference, 2013

2012
A Practical Regularity Partitioning Algorithm and its Applications in Clustering
CoRR, 2012

Clustered Knowledge Tracing.
Proceedings of the Intelligent Tutoring Systems - 11th International Conference, 2012

Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction.
Proceedings of the 5th International Conference on Educational Data Mining, 2012

The real world significance of performance prediction.
Proceedings of the 5th International Conference on Educational Data Mining, 2012

2011
Spectral Clustering in Educational Data Mining.
Proceedings of the 4th International Conference on Educational Data Mining, 2011

Clustering Students to Generate an Ensemble to Improve Standard Test Score Predictions.
Proceedings of the Artificial Intelligence in Education - 15th International Conference, 2011


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