Theja Tulabandhula

research

∙ 09/20/2023

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

We introduce Dynamic Tiling, a model-agnostic, adaptive, and scalable ap...

0 Son The Nguyen, et al. ∙

research

∙ 09/20/2023

Conformalized Multimodal Uncertainty Regression and Reasoning

This paper introduces a lightweight uncertainty estimator capable of pre...

0 Domenico Parente, et al. ∙

research

∙ 09/20/2023

STARNet: Sensor Trustworthiness and Anomaly Recognition via Approximated Likelihood Regret for Robust Edge Autonomy

Complex sensors such as LiDAR, RADAR, and event cameras have proliferate...

0 Nastaran Darabi, et al. ∙

research

∙ 09/18/2023

Mutual Information-calibrated Conformal Feature Fusion for Uncertainty-Aware Multimodal 3D Object Detection at the Edge

In the expanding landscape of AI-enabled robotics, robust quantification...

0 Alex C. Stutts, et al. ∙

research

∙ 08/27/2023

Generative AI for Business Strategy: Using Foundation Models to Create Business Strategy Tools

Generative models (foundation models) such as LLMs (large language model...

0 Son The Nguyen, et al. ∙

research

∙ 03/03/2023

Lightweight, Uncertainty-Aware Conformalized Visual Odometry

Data-driven visual odometry (VO) is a critical subroutine for autonomous...

0 Alex C. Stutts, et al. ∙

research

∙ 10/27/2022

Robust Monocular Localization of Drones by Adapting Domain Maps to Depth Prediction Inaccuracies

We present a novel monocular localization framework by jointly training ...

0 Priyesh Shukla, et al. ∙

research

∙ 07/05/2022

Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder

Graph theoretical analyses have become standard tools in modeling functi...

12 Carlo Amodeo, et al. ∙

research

∙ 04/25/2022

AI Personification: Estimating the Personality of Language Models

Technology for open-ended language generation, a key application of arti...

2 Saketh Reddy Karra, et al. ∙

research

∙ 04/12/2021

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

This work proposes a novel Energy-Aware Network Operator Search (ENOS) a...

15 Shamma Nasrin, et al. ∙

research

∙ 04/01/2021

Choice-Aware User Engagement Modeling andOptimization on Social Media

We address the problem of maximizing user engagement with content (in th...

9 Saketh Reddy Karra, et al. ∙

research

∙ 02/16/2021

Probabilistic Localization of Insect-Scale Drones on Floating-Gate Inverter Arrays

We propose a novel compute-in-memory (CIM)-based ultra-low-power framewo...

0 Priyesh Shukla, et al. ∙

research

∙ 12/21/2020

Off-Policy Optimization of Portfolio Allocation Policies under Constraints

The dynamic portfolio optimization problem in finance frequently require...

10 Nymisha Bandi, et al. ∙

research

∙ 12/06/2020

KATRec: Knowledge Aware aTtentive Sequential Recommendations

Sequential recommendation systems model dynamic preferences of users bas...

0 Mehrnaz Amjadi, et al. ∙

research

∙ 11/29/2020

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

This paper investigates the problem of assigning shipping requests to ad...

7 Tanvir Ahamed, et al. ∙

research

∙ 11/28/2020

Improved Optimistic Algorithm For The Multinomial Logit Contextual Bandit

We consider a dynamic assortment selection problem where the goal is to ...

6 Priyank Agrawal, et al. ∙

research

∙ 06/18/2020

Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect

We study the effect of persistence of engagement on learning in a stocha...

0 Priyank Agrawal, et al. ∙

research

∙ 06/14/2020

Multi-Purchase Behavior: Modeling and Optimization

We study the problem of modeling purchase of multiple items and utilizin...

0 Theja Tulabandhula, et al. ∙

research

∙ 03/06/2020

Optimizing Revenue while showing Relevant Assortments at Scale

Scalable real-time assortment optimization has become essential in e-com...

0 Theja Tulabandhula, et al. ∙

research

∙ 01/22/2020

Incentivising Exploration and Recommendations for Contextual Bandits with Payments

We propose a contextual bandit based model to capture the learning and s...

0 Priyank Agrawal, et al. ∙

research

∙ 11/19/2019

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

In this work, we introduce bitcell array-based support parameters to imp...

0 Shamma Nasrin, et al. ∙

research

∙ 01/23/2019

Thompson Sampling for a Fatigue-aware Online Recommendation System

In this paper we consider an online recommendation setting, where a plat...

0 Yunjuan Wang, et al. ∙

research

∙ 11/22/2018

Bandits with Temporal Stochastic Constraints

We study the effect of impairment on stochastic multi-armed bandits and ...

0 Priyank Agrawal, et al. ∙

research

∙ 04/24/2018

Block-Structure Based Time-Series Models For Graph Sequences

Although the computational and statistical trade-off for modeling single...

0 Mehrnaz Amjadi, et al. ∙

research

∙ 03/06/2018

An Online Algorithm for Learning Buyer Behavior under Realistic Pricing Restrictions

We propose a new efficient online algorithm to learn the parameters gove...

0 Debjyoti Saharoy, et al. ∙

research

∙ 10/09/2017

Privacy-preserving Targeted Advertising

Recommendation systems form the center piece of a rapidly growing trilli...

0 Theja Tulabandhula, et al. ∙

research

∙ 06/09/2017

Symmetry Learning for Function Approximation in Reinforcement Learning

In this paper we explore methods to exploit symmetries for ensuring samp...

0 Anuj Mahajan, et al. ∙

research

∙ 06/07/2017

Efficient Reinforcement Learning via Initial Pure Exploration

In several realistic situations, an interactive learning agent can pract...

0 Sudeep Raja Putta, et al. ∙

research

∙ 04/02/2017

Provable Inductive Robust PCA via Iterative Hard Thresholding

The robust PCA problem, wherein, given an input data matrix that is the ...

0 U. N. Niranjan, et al. ∙

research

∙ 09/18/2016

Learning Personalized Optimal Control for Repeatedly Operated Systems

We consider the problem of online learning of optimal control for repeat...

0 Theja Tulabandhula, et al. ∙

research

∙ 07/04/2014

Robust Optimization using Machine Learning for Uncertainty Sets

Our goal is to build robust optimization problems for making decisions b...

0 Theja Tulabandhula, et al. ∙

research

∙ 05/30/2014

Generalization Bounds for Learning with Linear, Polygonal, Quadratic and Conic Side Knowledge

In this paper, we consider a supervised learning setting where side know...

0 Theja Tulabandhula, et al. ∙

research

∙ 12/03/2011

Machine Learning with Operational Costs

This work proposes a way to align statistical modeling with decision mak...

0 Theja Tulabandhula, et al. ∙

research

∙ 04/27/2011

On Combining Machine Learning with Decision Making

We present a new application and covering number bound for the framework...

0 Theja Tulabandhula, et al. ∙

Theja Tulabandhula

Featured Co-authors