Now showing items 75-94 of 142

    • Latency-Tolerant Distributed Shared Memory For Data-Intensive Applications 

      Nelson, Jacob Eric
      Grappa is a modern take on software distributed shared memory (DSM) for in-memory data-intensive applications. Grappa enables users to program a cluster as if it were a single, large, non-uniform memory access (NUMA) ...
    • Learning and Exploiting Relational Structure for Efficient Inference 

      Nath, Aniruddh
      One of the central challenges of statistical relational learning is the tradeoff between expressiveness and computational tractability. Representations such as Markov logic can capture rich joint probabilistic models over ...
    • Leveraging Knowledge Bases in Web Text Processing 

      Lin, Thomas (2013-04-17)
      The Web contains more text than any other source in human history, and continues to expand rapidly. Computer algorithms to process and extract knowledge from Web text have the potential not only to improve Web search, but ...
    • Leveraging Usage History to Enhance Database Usability 

      Khoussainova, Nodira (2013-02-25)
      More so than ever before, large datasets are being collected and analyzed throughout a variety of disciplines. Examples include social networking data, software logs, scientific data, web clickstreams, sensor network data, ...
    • Lightweight structural summarization as an aid to software evolution 

      Murphy, Gail C. (Gail Cecile), 1965- (1996)
      To effectively perform a change to an existing software system, a software engineer needs to have some understanding of the structure of the system. All too often, though, an engineer must proceed to change a system without ...
    • Linguistically Motivated Combinatory Categorial Grammar Induction 

      Wang, Adrienne
      Combinatory Categorial Grammar (CCG) is a widely studied grammar formalism that has been used in a variety of NLP applications, e.g., semantic parsing, and machine translation. One key challenge in building effective CCG ...
    • Locati[o]n-based activity recognition 

      Liao, Lin (2006)
      Automatic recognition of human activities can support many applications, from context aware computing to just-in-time information systems to assistive technology for the disabled. Knowledge of a person's location provides ...
    • Low-depth quantum architectures for factoring 

      Pham, Paul (2014-02-24)
      Quantum computing is a new field which combines computer science and quantum physics. Its most famous result, Shor's factoring algorithm, would enable us to one day compromise the widely-used RSA cryptosystem if we are ...
    • Lowering the Barrier to Applying Machine Learning 

      Patel, Kayur Dushyant (2013-02-25)
      Data is driving the future of computation: analysis, visualization, and learning algorithms power systems that help us diagnose cancer, live sustainably, and understand the universe. Yet, the data explosion has outstripped ...
    • Machine learning as massive search 

      Segal, Richard B (1997)
      Machine learning is the inference of general patterns from data. Machine-learning algorithms search large spaces of potential hypotheses for the hypothesis that best fits the data. Since the search space for most induction ...
    • Machine Learning based Attacks and Defenses in Computer Security: Towards Privacy and Utility Balance in Emerging Technology Environments 

      Enev, Miroslav
      The growth of smart devices and the Internet of Things (IoT) is driving data markets in which users exchange sensor streams for services. In most current data exchange models, service providers offer their functionality ...
    • Managing Premium Data 

      Upadhyaya, Prasang
      Data is transforming science, business, and governance by making decisions increasingly data-driven and by enabling data-driven applications. The data used in these contexts usually has significant economic or social value. ...
    • Managing Skew in the Parallel Evaluation of User-Defined Operations 

      KWON, YONGCHUL (2013-02-25)
      Science and business are generating data at an unprecedented scale and rate due to ever evolving technologies in computing and sensors. Analyzing big data has become a key skill driving business and science. The challenges ...
    • Mobile Camera-Based Systems for Low-Resource Environments 

      Dell, Nicola Lee
      The suitability of mobile devices for data collection and decision support in developing countries has been well established. It is now relatively common for field workers to carry devices that help them decide what questions ...
    • Modeling Systems from Logs of their Behavior 

      Beschastnikh, Ivan (2013-07-25)
      Billions of people rely on correct and efficient execution of large systems, such as the distributed systems that power Google and Facebook. Yet these systems are complex and challenging to build and understand. Logging ...
    • Motif-based mining of protein sequences 

      Liu, Agatha H (2002)
      We introduce CASTOR, an automatic, unsupervised system for protein motif discovery and classification. Given amino acid sequences for a group of proteins, CASTOR generates statistically significant motifs and constructs a ...
    • Multi-versioned Data Storage and Iterative Processing in a Parallel Array Database Engine 

      Soroush, Emad
      Scientists today are able to generate data at an unprecedented scale and rate. For example the Sloan Digital Sky Survey (SDSS) generates 200GB of data containing millions of objects on each night on its routine operation. ...
    • New Techniques in Deep Representation Learning 

      Andrew, Galen Michael
      The choice of feature representation can have a large impact on the success of a machine learning algorithm at solving a given problem. Although human engineers employing task-specific domain knowledge still play a key ...
    • Object Recognition and Semantic Scene Labeling for RGB-D Data 

      Lai, Kevin Kar Wai (2014-02-24)
      The availability of RGB-D (Kinect-like) cameras has led to an explosive growth of research on robot perception. RGB-D cameras provide high resolution (640 x 480) synchronized videos of both color (RGB) and depth (D) at 30 ...
    • On profit maximization in mechanism design 

      Cary, Matthew, 1974- (2007)
      Mechanism design is a subfield of game theory and microeconomics focused on incentive engineering. A mechanism is a protocol, typically taking the form of an auction, that is explicitly designed so that rational but ...