Browsing by Subject "Computer science"
Now showing items 1-20 of 240
-
3D Object Representations for Robot Perception
(2019)Reasoning about 3D objects is one of the most critical perception problems robots face; outside of navigation, most interactions between a robot and its environment are object-centric. Object-centric robot perception has ... -
A Data-Intensive Framework for Analyzing Dynamic Supreme Court Behavior
(2012)Many law professors and scholars think of the Supreme Court as a black box--issues and arguments go in to the Court, and decisions come out. The almost mystical nature that these researchers impute to the Court seems to ... -
A Logical Controller Architecture for Network Security
(2020)Networked infrastructure-as-a-service testbeds are evolving with higher capacity and more advanced capabilities. Modern testbeds offer stitched virtual circuit capability, programmable dataplanes with software-defined networking ... -
A New Take on Gamification: Playing the Culture Shock Experience in a Digital Card Game
(2020)In 2018-2019, over 1 million international students from all over the world come to the United States to seek higher education. Along with their hope for quality education, they bring their own cultures. The clash of the ... -
A NEW ZEROTH-ORDER ORACLE FOR DISTRIBUTED AND NON-STATIONARY LEARNING
(2021)Zeroth-Order (ZO) methods have been applied to solve black-box or simulation-based optimization prroblems. These problems arise in many important applications nowa- days, e.g., generating adversarial attacks on machine learning ... -
A Privacy Preserving Algorithm to Release Sparse High-dimensional Histograms
(2017)Differential privacy (DP) aims to design methods and algorithms that satisfy rigorous notions of privacy while simultaneously providing utility with valid statistical inference. More recently, an emphasis has been placed ... -
A Q-Learning Approach to Minefield Characterization from Unmanned Aerial Vehicles
(2012)The treasure hunt problem to determine how a computational agent can maximize its ability to detect and/or classify multiple targets located in a region of interest (ROI) populated with multiple obstacles. One particular ... -
A Semi-Supervised Predictive Model to Link Regulatory Regions to Their Target Genes
(2015)Next generation sequencing technologies have provided us with a wealth of data profiling a diverse range of biological processes. In an effort to better understand the process of gene regulation, two predictive machine learning ... -
A Theoretical and Experimental Study of DNA Self-assembly
(2012)The control of matter and phenomena at the nanoscale is fast becoming one of the most important challenges of the 21st century with wide-ranging applications from energy and health care to computing and material science. ... -
Accelerating Data Parallel Applications via Hardware and Software Techniques
(2020)The unprecedented amount of data available today opens the door to many new applications in areas such as finance, scientific simulation, machine learning, etc. Many such applications perform the same computations on different ... -
Accelerator Architectures for Deep Learning and Graph Processing
(2020)Deep learning and graph processing are two big-data applications and they are widely applied in many domains. The training of deep learning is essential for inference and has not yet been fully studied. With data forward, ... -
Advancing the Design and Utility of Adversarial Machine Learning Methods
(2021)While significant progress has been made to craft Deep Neural Networks (DNNs) with super-human recognition performance, their reliability and robustness in challenging operating conditions is still a major concern. In this ... -
Algorithms for Allocation Problems in Online Settings
(2018)A fundamental computational challenge that arises in the operation of online systems, services, and platforms is that of resource allocation. Broadly defined, a resource allocation problem is one where set of users generate ... -
Algorithms for Analyzing Spatio-Temporal Data
(2018)In today's age, huge data sets are becoming ubiquitous. In addition to their size, most of these data sets are often noisy, have outliers, and are incomplete. Hence, analyzing such data is challenging. We look at applying ... -
Algorithms for Clustering, Partitioning, and Planning
(2023)We explore three geometric optimization problems with multifaceted goals, including efficiency, fairness, solution quality, and interpretability. The problems we study pose significant challenges because they involve complex ... -
Algorithms for continuous queries: A geometric approach
(2013)There has been an unprecedented growth in both the amount of data and the number of users interested in different types of data. Users often want to keep track of the data that match their interests over a period of time. ... -
Algorithms for Geometric Matching, Clustering, and Covering
(2016)With the popularization of GPS-enabled devices such as mobile phones, location data are becoming available at an unprecedented scale. The locations may be collected from many different sources such as vehicles moving around ... -
Algorithms for Networks With Uncertainty
(2019)In this dissertation, we study algorithmic problems motivated by the optimization of networks under uncertainty.We summarize our contributions:\begin{itemize}\item \textbf{Subset $k$-server:} We propose and give algorithms ... -
Algorithms for Public Decision Making
(2019)In public decision making, we are confronted with the problem of aggregating the conflicting preferences of many individuals about outcomes that affect the group. Examples of public decision making include allocating shared ... -
Algorithms for Rectangular Robot Motion Planning
(2023)With the proliferation of robot deployment in large-scale operations, such as warehouse management and manufacturing, there is an increasing need for multi-robot motion planning solutions. The basic multi-robot motion planning ...
