Theja Tulabandhula

Orcid: 0000-0001-9111-7519

According to our database1, Theja Tulabandhula authored at least 77 papers between 2008 and 2024.

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

Timeline

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Bibliography

2024
Enhancing 3D Robotic Vision Robustness by Minimizing Adversarial Mutual Information through a Curriculum Training Approach.
CoRR, 2024

Sense Less, Generate More: Pre-training LiDAR Perception with Masked Autoencoders for Ultra-Efficient 3D Sensing.
CoRR, 2024

CURATRON: Complete Robust Preference Data for Robust Alignment of Large Language Models.
CoRR, 2024

Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement Learning.
CoRR, 2024

InteraRec: Interactive Recommendations Using Multimodal Large Language Models.
Proceedings of the Trends and Applications in Knowledge Discovery and Data Mining, 2024

STARNet: Sensor Trustworthiness and Anomaly Recognition via Lightweight Likelihood Regret for Robust Edge Autonomy.
Proceedings of the International Joint Conference on Neural Networks, 2024

Mutual Information-calibrated Conformal Feature Fusion for Uncertainty-Aware Multimodal 3D Object Detection at the Edge.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Conformalized Multimodal Uncertainty Regression and Reasoning.
Proceedings of the IEEE International Conference on Acoustics, 2024

Invited: Conformal Inference meets Evidential Learning: Distribution-Free Uncertainty Quantification with Epistemic and Aleatoric Separability.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023
A tractable online learning algorithm for the multinomial logit contextual bandit.
Eur. J. Oper. Res., October, 2023

A Novel Approach to Clustering Accelerometer Data for Application in Passive Predictions of Changes in Depression Severity.
Sensors, February, 2023

User Friendly and Adaptable Discriminative AI: Using the Lessons from the Success of LLMs and Image Generation Models.
CoRR, 2023

InteraSSort: Interactive Assortment Planning Using Large Language Models.
CoRR, 2023

Dynamic Tiling: A Model-Agnostic, Adaptive, Scalable, and Inference-Data-Centric Approach for Efficient and Accurate Small Object Detection.
CoRR, 2023

STARNet: Sensor Trustworthiness and Anomaly Recognition via Approximated Likelihood Regret for Robust Edge Autonomy.
CoRR, 2023

Generative AI for Business Strategy: Using Foundation Models to Create Business Strategy Tools.
CoRR, 2023

Lightweight, Uncertainty-Aware Conformalized Visual Odometry.
IROS, 2023

Robust Monocular Localization of Drones by Adapting Domain Maps to Depth Prediction Inaccuracies.
Proceedings of the IEEE International Conference on Acoustics, 2023

Smartphone-derived Virtual Keyboard Dynamics Coupled with Accelerometer Data as a Window into Understanding Brain Health: Smartphone Keyboard and Accelerometer as Window into Brain Health.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022
Ultralow-Power Localization of Insect-Scale Drones: Interplay of Probabilistic Filtering and Compute-in-Memory.
IEEE Trans. Very Large Scale Integr. Syst., 2022

Optimizing revenue while showing relevant assortments at scale.
Eur. J. Oper. Res., 2022

AI Personification: Estimating the Personality of Language Models.
CoRR, 2022

ENOS: Energy-Aware Network Operator Search in Deep Neural Networks.
IEEE Access, 2022

Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021
ENOS: Energy-Aware Network Operator Search for Hybrid Digital and Compute-in-Memory DNN Accelerators.
CoRR, 2021

Choice-Aware User Engagement Modeling andOptimization on Social Media.
CoRR, 2021

KATRec: Knowledge Aware aTtentive Sequential Recommendations.
Proceedings of the Discovery Science - 24th International Conference, 2021

2020
Off-Policy Optimization of Portfolio Allocation Policies under Constraints.
CoRR, 2020

KATRec: Knowledge Aware aTtentive Sequential Recommendations.
CoRR, 2020

Deep Reinforcement Learning for Crowdsourced Urban Delivery: System States Characterization, Heuristics-guided Action Choice, and Rule-Interposing Integration.
CoRR, 2020

Improved Optimistic Algorithm For The Multinomial Logit Contextual Bandit.
CoRR, 2020

Multi-Purchase Behavior: Modeling and Optimization.
CoRR, 2020

Optimizing Revenue while showing Relevant Assortments at Scale.
CoRR, 2020

MC<sup>2</sup>RAM: Markov Chain Monte Carlo Sampling in SRAM for Fast Bayesian Inference.
CoRR, 2020

Recommendations under Multi-Product Purchase Behavior.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

MC2RAM: Markov Chain Monte Carlo Sampling in SRAM for Fast Bayesian Inference.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

Supported-BinaryNet: Bitcell Array-Based Weight Supports for Dynamic Accuracy-Energy Trade-Offs in SRAM-Based Binarized Neural Network.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

Making Recommendations when Users Experience Fatigue.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2020

Incentivising Exploration and Recommendations for Contextual Bandits with Payments.
Proceedings of the Multi-Agent Systems and Agreement Technologies, 2020

2019
Real-Time Hybrid Multi-Sensor Fusion Framework for Perception in Autonomous Vehicles.
Sensors, 2019

Supported-BinaryNet: Bitcell Array-based Weight Supports for Dynamic Accuracy-Latency Trade-offs in SRAM-based Binarized Neural Network.
CoRR, 2019

Thompson Sampling for a Fatigue-aware Online Recommendation System.
CoRR, 2019

Managing adoption under network effects.
Proceedings of the 14th Workshop on the Economics of Networks, Systems and Computation, 2019

2018
Bandits with Temporal Stochastic Constraints.
CoRR, 2018

Block-Structure Based Time-Series Models For Graph Sequences.
CoRR, 2018

An Online Algorithm for Learning Buyer Behavior under Realistic Pricing Restrictions.
CoRR, 2018

Learning Buyer Behavior under Realistic Pricing Restrictions.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2018

Impact of Detour-Aware Policies on Maximizing Profit in Ridesharing.
Proceedings of the Tenth International Workshop on Agents in Traffic and Transportation (ATT 2018) co-located with with the Federated Artificial Intelligence Meeting, 2018

2017
Privacy-preserving Targeted Advertising.
CoRR, 2017

Optimizing Revenue over Data-driven Assortments.
CoRR, 2017

Efficient Reinforcement Learning via Initial Pure Exploration.
CoRR, 2017

Symmetry Learning for Function Approximation in Reinforcement Learning.
CoRR, 2017

Faster Reinforcement Learning Using Active Simulators.
CoRR, 2017

Interactions between learning and decision making.
AI Matters, 2017

Provable Inductive Robust PCA via Iterative Hard Thresholding.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Learning to Partition using Score Based Compatibilities.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Pure Exploration in Episodic Fixed-Horizon Markov Decision Processes.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Symmetry Detection and Exploitation for Function Approximation in Deep RL.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Profit Optimization in Commercial Ridesharing.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

2016
Learning Personalized Optimal Control for Repeatedly Operated Systems.
CoRR, 2016

Reinforcement Learning algorithms for regret minimization in structured Markov Decision Processes.
CoRR, 2016

The Costs and Benefits of Ridesharing: Sequential Individual Rationality and Sequential Fairness.
CoRR, 2016

Reinforcement Learning Algorithms for Regret Minimization in Structured Markov Decision Processes: (Extended Abstract).
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

2015
Generalization bounds for learning with linear, polygonal, quadratic and conic side knowledge.
Mach. Learn., 2015

2014
Interactions between learning and decision making.
PhD thesis, 2014

On combining machine learning with decision making.
Mach. Learn., 2014

Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing.
Big Data, 2014

Robust Optimization using Machine Learning for Uncertainty Sets.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2014

Generalization Bounds for Learning with Linear and Quadratic Side Knowledge.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2014

2013
Machine learning with operational costs.
J. Mach. Learn. Res., 2013

2012
The Influence of Operational Cost on Estimation.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2012

2011
Machine Learning and the Traveling Repairman
CoRR, 2011

The Machine Learning and Traveling Repairman Problem.
Proceedings of the Algorithmic Decision Theory - Second International Conference, 2011

2010
Some Architectures for Chebyshev Interpolation
CoRR, 2010

2009
A 20MS/s 5.6 mW 6b Asynchronous ADC in 0.6µm CMOS.
Proceedings of the VLSI Design 2009: Improving Productivity through Higher Abstraction, 2009

2008
Design of a Two Dimensional PRSI Image Processor.
Proceedings of the 11th Euromicro Conference on Digital System Design: Architectures, 2008


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