Phd Dissertation Computer Science

Phd Dissertation Computer Science-23
To fulfill requirements for the Thesis option, students must satisfy the breadth requirement, adhere to an appropriate credit distribution, enroll in the graduate seminar, comply with the ethics and diversity requirements, and complete an oral and written final exam (also known as a Master's Thesis).

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PDF Network-aware energy saving techniques in cloud data centers, Motassem Al-Tarazi PDF Situation-oriented requirements engineering, Nimanthi Atukorala PDF The construction and applications of callback control flow graphs for event-driven and framework-based mobile apps, Danilo Dominguez Perez PDF Witness generation in existential CTL model checking, Chuan Jiang PDF Nonparametric curve estimation and applications, Yu Liu PDF Taking the lab on the road and bringing the road to the lab: On using mixed-methods and virtual reality to study a location-based task, Kofi Whitney PDF Toward efficient online scheduling for large-scale distributed machine learning system, Menglu Yu PDF Medical image classification under class imbalance, Chuanhai Zhang PDF Automatic incident detection, Lakshay Ahuja PDF Enhancing users' experiences with mobile app stores: What do users see? Stull PDF The design and implementation of Candoia: A platform for building and sharing mining software repositories tools as apps, Nitin Mukesh Tiwari PDF Learning Markov Logic Network Structure by Template Constructing, Yingbei Tong PDF Computational modeling of impact and deformation, Feifei Wang PDF Execution and authentication of function queries, Guolei Yang PDF A situation-centric, knowledge-driven requirements elicitation approach, Jingwei Yang PDF Syntax errors identification from compiler error messages using ML techniques, Shubham K.

Asiri PDF Disrupting diffusion: Critical nodes in network, Preeti Bhardwaj PDF Recognition of activities of daily living, Yunfei Feng PDF A data-driven situation-aware framework for predictive analysis in smart environments, Hoda Gholami PDF Effectiveness of classification approach in recovering pairwise causal relations from data., Kristima Guha Thakurta PDF A study of interpretability mechanisms for deep networks, Apurva Dilip Kokate PDF Large-scale study of substitutability in the presence of effects, Jackson Lowell Maddox PDF Towards efficient and accountable oblivious cloud storage, Qiumao Ma PDF Improved triangle counting in graph streams: Neighborhood multi-sampling, Kiana Mousavi Hanjani PDF High performance computing applications: Inter-process communication, workflow optimization, and deep learning for computational nuclear physics, Gianina Alina Negoita PDF Data augmentation for supervised learning with generative adversarial networks, Manaswi Podduturi PDF Graph compression using heuristic-based reordering, Pavithra Rajarathinam PDF Collective program analysis, Ganesha Upadhyaya PDF Graph Track: An unsupervised graph-based cross-device tracking framework, Tianchen Zhou PDF Improving testing performance by dynamic prioritization of tests based on method invocation orders, Sriram Balasubramanian PDF Computer detection of spatial visualization in a location-based task, Georgi Iliev Batinov PDF A User Configurable B-tree Implementation as a Utility, Sheng Bi PDF Devices for safety-critical molecular programmed systems, Samuel Jay Ellis PDF A testbed for multi-robot systems, Tianshuang Gao PDF Many-to-one private set intersection, Keji Hu PDF Parity-based Data Outsourcing: Extension, Implementation, and Evaluation, Zhenbi Hu PDF Computing change of invariants to support software evolution, Ashwin Kallingal Joshy PDF Triangle counting in graph streams: Power of multi-sampling, Neeraj Kavassery Parakkat PDF Exploiting implicit belief to resolve sparse usage problem in usage-based specification mining, Samantha Syeda Khairunnesa PDF Synthesizing species trees from gene trees using the parameterized and graph-theoretic approaches, Ju Cheol Moon PDF Verification of Well-formedness in Message-Passing Asynchronous Systems modeled as Communicating Finite-State Machines, Shiva Shankar Nalla PDF Negotiation Based Resource Allocation to Control Information Diffusion, Sai Sravanthi Nudurupati PDF Flattening methods for adaptive location-based software to user abilities, Thitivatr Patanasakpinyo PDF λir : A language with intensional receive, Swarn Priya PDF A hybrid approach for selecting and optimizing graph traversal strategy for analyzing big code, Ramanathan Ramu PDF Targeted Influence Maximization In Labeled Social Networks with Non-Target Constraints, Naresh Somisetty PDF Algorithmic randomness and analysis, Donald M.

Bowers, Computer Science PDF Exploiting Concepts In Videos For Video Event Detection, Ethem Can, Computer Science PDF Learning Parameterized Skills, Bruno Castro da Silva, Computer Science PDF Robust Mobile Data Transport: Modeling, Measurements, and Implementation, Yung-Chih Chen, Computer Science PDF Model-Based Guidance for Human-Intensive Processes, Stefan Christov, Computer Science PDF General Program Synthesis from Examples Using Genetic Programming with Parent Selection Based on Random Lexicographic Orderings of Test Cases, Thomas Helmuth, Computer Science PDF Network Characteristics and Dynamics: Reciprocity, Competition and Information Dissemination, Bo Jiang, Computer Science PDF Application of Techniques for MAP Estimation to Distributed Constraint Optimization Problem, Yoonheui Kim, Computer Science PDF Exploiting Social Media Sources for Search, Fusion and Evaluation, Chia-Jung Lee, Computer Science PDF A Platform for Scalable Low-Latency Analytics using Map Reduce, Boduo Li, Computer Science PDF Energy-Efficient Content Delivery Networks, Vimal Mathew, Computer Science PDF Energy Optimizations for Smart Buildings and Smart Grids, Aditya K.

Mishra, Computer Science PDF Learning with Joint Inference and Latent Linguistic Structure in Graphical Models, Jason Narad, Computer Science PDF Long Range Motion Estimation and Applications, Laura Sevilla-Lara, Computer Science PDF Content Placement as a Key to a Content-Dominated, Highly mobile Internet, Abhigyan Sharma, Computer Science PDF Variation in Human-Intensive Systems: a Conceptual Framework for Characterizing, Modeling, and Analyzing Families of Systems, Borislava I.

NYU Poly students have access to a broad range of research tools and a huge volume of literature in all areas of Computer Science and Engineering.

Phd Dissertation Computer Science

This guide is designed to help you decide what kind of resources you need and to introduce you to the best tools and strategies for finding them.Altidor, Computer Science PDF Model-Driven Analytics of Energy Meter Data in Smart Homes, Sean K.Crouch, Computer Science PDF ADAPTIVE STEP-SIZES FOR REINFORCEMENT LEARNING, William C.Earlier instances of the courses do not cover the required training, and so cannot be used.) Note: Each of the lines above must be interpreted as an individual, distinct, constraint so that all constraints have to be simultaneously satisfied.The columns are not meant to "add up", i.e., 30 6 3 is obviously not equal to 30.Phan, Computer Science PDF Specification and Analysis of Resource Utilization Policies for Human-Intensive Systems, Seung Yeob Shin, Computer Science PDF Intrinsically Motivated Exploration in Hierarchical Reinforcement Learning, Christopher M.Vigorito, Computer Science PDF Stochastic Network Design: Models and Scalable Algorithms, Xiaojian Wu, Computer Science PDF Leveraging Backscatter for Ultra-low Power Wireless Sensing Systems, PENGYU ZHANG, Computer Science PDF Shape Design and Optimization for 3D Printing, Yahan Zhou, Computer Science PDF Reconstructing Geometric Structures from Combinatorial and Metric Information, Md Ashraful Alam, Computer Science PDF An Analysis of Student Learning Strategies in High Enrollment Computer-Based College Courses, gordon c.The CS Department also requires students to take a minimum number of instances of CS5944 Graduate Seminar.Students entering the program in Summer 2019 or after must do the following.Simidchieva, Computer Science PDF Informed Search for Learning Causal Structure, Brian J.Taylor, Computer Science PDF Safe Reinforcement Learning, Philip S.

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