Design of a Two Dimensional PRSI Image Processor. - Theja Tulabandhula; Amit Patra; Nirmal B. Chakrabarti (DSD, 2008)

A 20MS/s 5.6 mW 6b Asynchronous ADC in 0.6µm CMOS. - Theja Tulabandhula; Yujendra Mitikiri (VLSI Design, 2009)

Some Architectures for Chebyshev Interpolation - Theja Tulabandhula (CoRR, 2010)

The Machine Learning and Traveling Repairman Problem. - Theja Tulabandhula; Cynthia Rudin; Patrick Jaillet (ADT, 2011)

Machine Learning and the Traveling Repairman - Theja Tulabandhula; Cynthia Rudin; Patrick Jaillet (CoRR, 2011)

The Influence of Operational Cost on Estimation. - Cynthia Rudin; Theja Tulabandhula (ISAIM, 2012)

Machine learning with operational costs. - Theja Tulabandhula; Cynthia Rudin (J. Mach. Learn. Res., 2013)

Generalization Bounds for Learning with Linear and Quadratic Side Knowledge. - Theja Tulabandhula; Cynthia Rudin (ISAIM, 2014)

Robust Optimization using Machine Learning for Uncertainty Sets. - Theja Tulabandhula; Cynthia Rudin (ISAIM, 2014)

Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing. - Theja Tulabandhula; Cynthia Rudin (Big Data, 2014)

On combining machine learning with decision making. - Theja Tulabandhula; Cynthia Rudin (Mach. Learn., 2014)

Interactions between learning and decision making. - Theja Tulabandhula (2014)

Generalization bounds for learning with linear, polygonal, quadratic and conic side knowledge. - Theja Tulabandhula; Cynthia Rudin (Mach. Learn., 2015)

Reinforcement Learning Algorithms for Regret Minimization in Structured Markov Decision Processes: (Extended Abstract). - Prabuchandran K. J.; Tejas Bodas; Theja Tulabandhula (AAMAS, 2016)

The Costs and Benefits of Ridesharing: Sequential Individual Rationality and Sequential Fairness. - Ragavendran Gopalakrishnan; Koyel Mukherjee; Theja Tulabandhula (CoRR, 2016)

Reinforcement Learning algorithms for regret minimization in structured Markov Decision Processes. - Prabuchandran K. J.; Tejas Bodas; Theja Tulabandhula (CoRR, 2016)

Learning Personalized Optimal Control for Repeatedly Operated Systems. - Theja Tulabandhula (CoRR, 2016)

Profit Optimization in Commercial Ridesharing. - Arpita Biswas; Ragavendran Gopalakrishnan; Theja Tulabandhula; Koyel Mukherjee; Asmita Metrewar; Thangaraj Rajasubramaniam (AAMAS, 2017)

Symmetry Detection and Exploitation for Function Approximation in Deep RL. - Anuj Mahajan; Theja Tulabandhula (AAMAS, 2017)

Pure Exploration in Episodic Fixed-Horizon Markov Decision Processes. - Sudeep Raja Putta; Theja Tulabandhula (AAMAS, 2017)

Learning to Partition using Score Based Compatibilities. - Arun Rajkumar; Koyel Mukherjee; Theja Tulabandhula (AAMAS, 2017)

Provable Inductive Robust PCA via Iterative Hard Thresholding. - U. N. Niranjan; Arun Rajkumar; Theja Tulabandhula (UAI, 2017)

Interactions between learning and decision making. - Theja Tulabandhula (AI Matters, 2017)

Faster Reinforcement Learning Using Active Simulators. - Vikas Jain; Theja Tulabandhula (CoRR, 2017)

Symmetry Learning for Function Approximation in Reinforcement Learning. - Anuj Mahajan; Theja Tulabandhula (CoRR, 2017)

Efficient Reinforcement Learning via Initial Pure Exploration. - Sudeep Raja Putta; Theja Tulabandhula (CoRR, 2017)

Optimizing Revenue over Data-driven Assortments. - Deeksha Sinha; Theja Tulabandhula (CoRR, 2017)

Privacy-preserving Targeted Advertising. - Theja Tulabandhula; Shailesh Vaya; Aritra Dhar (CoRR, 2017)

Impact of Detour-Aware Policies on Maximizing Profit in Ridesharing. - Arpita Biswas; Ragavendran Gopalakrishnan; Theja Tulabandhula; Asmita Metrewar; Koyel Mukherjee; Raja Subramaniam Thangaraj (ATT@IJCAI, 2018)

Learning Buyer Behavior under Realistic Pricing Restrictions. - Debjyoti Saharoy; Theja Tulabandhula (ISAIM, 2018)

An Online Algorithm for Learning Buyer Behavior under Realistic Pricing Restrictions. - Debjyoti Saharoy; Theja Tulabandhula (CoRR, 2018)

Block-Structure Based Time-Series Models For Graph Sequences. - Mehrnaz Amjadi; Theja Tulabandhula (CoRR, 2018)

Bandits with Temporal Stochastic Constraints. - Priyank Agrawal; Theja Tulabandhula (CoRR, 2018)

Managing adoption under network effects. - Mehrnaz Amjadi; Vijay Kamble; Theja Tulabandhula (NetEcon@SIGMETRICS, 2019)

Thompson Sampling for a Fatigue-aware Online Recommendation System. - Yunjuan Wang; Theja Tulabandhula (CoRR, 2019)

Supported-BinaryNet: Bitcell Array-based Weight Supports for Dynamic Accuracy-Latency Trade-offs in SRAM-based Binarized Neural Network. - Shamma Nasrin; Srikanth Ramakrishna; Theja Tulabandhula; Amit Ranjan Trivedi (CoRR, 2019)

Real-Time Hybrid Multi-Sensor Fusion Framework for Perception in Autonomous Vehicles. - Babak Shahian Jahromi; Theja Tulabandhula; Sabri Cetin (Sensors, 2019)

Incentivising Exploration and Recommendations for Contextual Bandits with Payments. - Priyank Agrawal; Theja Tulabandhula (EUMAS/AT, 2020)

Making Recommendations when Users Experience Fatigue. - Theja Tulabandhula; Yunjuan Wang (ISAIM, 2020)

Supported-BinaryNet: Bitcell Array-Based Weight Supports for Dynamic Accuracy-Energy Trade-Offs in SRAM-Based Binarized Neural Network. - Shamma Nasrin; Srikanth Ramakrishna; Theja Tulabandhula; Amit Ranjan Trivedi (ISCAS, 2020)

MC2RAM: Markov Chain Monte Carlo Sampling in SRAM for Fast Bayesian Inference. - Priyesh Shukla; Ahish Shylendra; Theja Tulabandhula; Amit Ranjan Trivedi (ISCAS, 2020)

Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect. - Priyank Agrawal; Theja Tulabandhula (UAI, 2020)

Recommendations under Multi-Product Purchase Behavior. - Theja Tulabandhula; Deeksha Sinha; Prasoon Patidar (WWW (Companion Volume), 2020)

MC2RAM: Markov Chain Monte Carlo Sampling in SRAM for Fast Bayesian Inference. - Priyesh Shukla; Ahish Shylendra; Theja Tulabandhula; Amit Ranjan Trivedi (CoRR, 2020)

Optimizing Revenue while showing Relevant Assortments at Scale. - Theja Tulabandhula; Deeksha Sinha (CoRR, 2020)

Multi-Purchase Behavior: Modeling and Optimization. - Theja Tulabandhula; Deeksha Sinha; Prasoon Patidar (CoRR, 2020)

Improved Optimistic Algorithm For The Multinomial Logit Contextual Bandit. - Priyank Agrawal; Vashist Avadhanula; Theja Tulabandhula (CoRR, 2020)

Deep Reinforcement Learning for Crowdsourced Urban Delivery: System States Characterization, Heuristics-guided Action Choice, and Rule-Interposing Integration. - Tanvir Ahamed; Bo Zou; Nahid Parvez Farazi; Theja Tulabandhula (CoRR, 2020)

KATRec: Knowledge Aware aTtentive Sequential Recommendations. - Mehrnaz Amjadi; Danial Mohseni-Taheri; Theja Tulabandhula (CoRR, 2020)

Off-Policy Optimization of Portfolio Allocation Policies under Constraints. - Nymisha Bandi; Theja Tulabandhula (CoRR, 2020)

KATRec: Knowledge Aware aTtentive Sequential Recommendations. - Mehrnaz Amjadi; Seyed Danial Mohseni Taheri; Theja Tulabandhula (DS, 2021)

Choice-Aware User Engagement Modeling andOptimization on Social Media. - Saketh Reddy Karra; Theja Tulabandhula (CoRR, 2021)

ENOS: Energy-Aware Network Operator Search for Hybrid Digital and Compute-in-Memory DNN Accelerators. - Shamma Nasrin; Ahish Shylendra; Yuti Kadakia; Nick Iliev; Wilfred Gomes; Theja Tulabandhula; Amit Ranjan Trivedi (CoRR, 2021)

Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder. - Carlo Amodeo; Igor Fortel; Olusola Ajilore; Liang Zhan; Alex D. Leow; Theja Tulabandhula (MICCAI (1), 2022)

ENOS: Energy-Aware Network Operator Search in Deep Neural Networks. - Shamma Nasrin; Ahish Shylendra; Nastaran Darabi; Theja Tulabandhula; Wilfred Gomes; Ankush Chakrabarty; Amit Ranjan Trivedi (IEEE Access, 2022)

AI Personification: Estimating the Personality of Language Models. - Saketh Reddy Karra; Son Nguyen; Theja Tulabandhula (CoRR, 2022)

Optimizing revenue while showing relevant assortments at scale. - Theja Tulabandhula; Deeksha Sinha; Saketh Reddy Karra (Eur. J. Oper. Res., 2022)

Ultralow-Power Localization of Insect-Scale Drones: Interplay of Probabilistic Filtering and Compute-in-Memory. - Priyesh Shukla; Ankith Muralidhar; Nick Iliev; Theja Tulabandhula; Sawyer B. Fuller; Amit Ranjan Trivedi (IEEE Trans. Very Large Scale Integr. Syst., 2022)

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. - Emma Ning; Andrea T. Cladek; Mindy K. Ross; Sarah Kabir; Amruta Barve; Ellyn Kennelly; Faraz Hussain 002; Jennifer Duffecy; Scott L. Langenecker; Theresa Nguyen; Theja Tulabandhula; John Zulueta; et al. (CHI, 2023)

Robust Monocular Localization of Drones by Adapting Domain Maps to Depth Prediction Inaccuracies. - Priyesh Shukla; Sureshkumar S.; Alex C. Stutts; Sathya Ravi; Theja Tulabandhula; Amit Ranjan Trivedi (ICASSP, 2023)

Lightweight, Uncertainty-Aware Conformalized Visual Odometry. - Alex C. Stutts; Danilo Erricolo; Theja Tulabandhula; Amit Ranjan Trivedi (IROS, 2023)

Generative AI for Business Strategy: Using Foundation Models to Create Business Strategy Tools. - Son The Nguyen; Theja Tulabandhula (CoRR, 2023)

STARNet: Sensor Trustworthiness and Anomaly Recognition via Approximated Likelihood Regret for Robust Edge Autonomy. - Nastaran Darabi; Sina Tayebati; Sureshkumar S.; Sathya Ravi; Theja Tulabandhula; Amit Ranjan Trivedi (CoRR, 2023)

Dynamic Tiling: A Model-Agnostic, Adaptive, Scalable, and Inference-Data-Centric Approach for Efficient and Accurate Small Object Detection. - Son The Nguyen; Theja Tulabandhula; Duy Nguyen (CoRR, 2023)

InteraSSort: Interactive Assortment Planning Using Large Language Models. - Saketh Reddy Karra; Theja Tulabandhula (CoRR, 2023)

User Friendly and Adaptable Discriminative AI: Using the Lessons from the Success of LLMs and Image Generation Models. - Son The Nguyen; Theja Tulabandhula; Mary Beth Watson-Manheim (CoRR, 2023)

A Novel Approach to Clustering Accelerometer Data for Application in Passive Predictions of Changes in Depression Severity. - Mindy K. Ross; Theja Tulabandhula; Casey C. Bennett; Eu-Gene Baek; Dohyeon Kim; Faraz Hussain 002; Alexander P. Demos; Emma Ning; Scott A. Langenecker; Olusola Ajilore; Alex D. Leow (Sensors, 2023)

A tractable online learning algorithm for the multinomial logit contextual bandit. - Priyank Agrawal; Theja Tulabandhula; Vashist Avadhanula (Eur. J. Oper. Res., 2023)

Invited: Conformal Inference meets Evidential Learning: Distribution-Free Uncertainty Quantification with Epistemic and Aleatoric Separability. - Alex Christopher Stutts; Divake Kumar; Theja Tulabandhula; Amit Ranjan Trivedi (DAC, 2024)

Conformalized Multimodal Uncertainty Regression and Reasoning. - Domenico Parente; Nastaran Darabi; Alex C. Stutts; Theja Tulabandhula; Amit Ranjan Trivedi (ICASSP, 2024)

Mutual Information-calibrated Conformal Feature Fusion for Uncertainty-Aware Multimodal 3D Object Detection at the Edge. - Alex C. Stutts; Danilo Erricolo; Sathya Ravi; Theja Tulabandhula; Amit Ranjan Trivedi (ICRA, 2024)

STARNet: Sensor Trustworthiness and Anomaly Recognition via Lightweight Likelihood Regret for Robust Edge Autonomy. - Nastaran Darabi; Sina Tayebati; Sureshkumar Senthilkumar; Dinithi Jayasuriya; Sathya Ravi; Theja Tulabandhula; Amit Ranjan Trivedi (IJCNN, 2024)

InteraRec: Interactive Recommendations Using Multimodal Large Language Models. - Saketh Reddy Karra; Theja Tulabandhula (PAKDD (Workshops), 2024)

Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement Learning. - Alex Christopher Stutts; Danilo Erricolo; Theja Tulabandhula; Amit Ranjan Trivedi (CoRR, 2024)

CURATRON: Complete Robust Preference Data for Robust Alignment of Large Language Models. - Son The Nguyen; Uma-Naresh Niranjan; Theja Tulabandhula (CoRR, 2024)

Sense Less, Generate More: Pre-training LiDAR Perception with Masked Autoencoders for Ultra-Efficient 3D Sensing. - Sina Tayebati; Theja Tulabandhula; Amit Ranjan Trivedi (CoRR, 2024)

Enhancing 3D Robotic Vision Robustness by Minimizing Adversarial Mutual Information through a Curriculum Training Approach. - Nastaran Darabi; Dinithi Jayasuriya; Devashri Naik; Theja Tulabandhula; Amit Ranjan Trivedi (CoRR, 2024)

Generative Sensing: Pre-training LiDAR with Masked Autoencoders for Ultra-Frugal Perception. - Sina Tayebati; Theja Tulabandhula; Amit Ranjan Trivedi (ICASSP, 2025)

Prediction of Lung Metastasis from Hepatocellular Carcinoma using the SEER Database. - Jeff J. H. Kim; George R. Nahass; Yang Dai; Theja Tulabandhula (CoRR, 2025)

An application of deep choice modeling for engagement maximization on Twitter/X. - Saketh Reddy Karra; Theja Tulabandhula (J. Intell. Inf. Syst., 2025)

MEMETRON: Metaheuristic Mechanisms for Test-time Response Optimization of Large Language Models. - Son The Nguyen; Theja Tulabandhula (CoRR, 2025)