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1 - 25 of 4
| Creator | Title | Description | Subject | Date | ||
|---|---|---|---|---|---|---|
| 1 |
 | Venkatasubramanian, Suresh | Approximate Bregman near neighbors in sublinear time: beyond the triangle inequality | Bregman divergences are important distance measures that are used extensively in data-driven applications such as computer vision, text mining, and speech processing, and are a key focus of interest in machine learning. Answering nearest neighbor (NN) queries under these measures is very important i... | 2012-01-01 | |
| 2 |
 | Regehr, John | Efficient memory safety for TinyOS | Reliable sensor network software is difficult to create: applications are concurrent and distributed, hardware-based memory protection is unavailable, and severe resource constraints necessitate the use of unsafe, low-level languages. Our work improves this situation by providing efficient memory an... | 2007-01-01 | |
| 3 |
 | Regehr, John | Eliminating stack overflow by abstract interpretation | An important correctness criterion for software running on embedded microcontrollers is stack safety: a guarantee that the call stack does not overflow. Our first contribution is a method for statically guaranteeing stack safety of interrupt-driven embedded software using an approach based on contex... | 2005-01-01 | |
| 4 |
 | Regehr, John | Pluggable abstract domains for analyzing embedded software | Many abstract value domains such as intervals, bitwise, constants, and value-sets have been developed to support dataflow analysis. Different domains offer alternative tradeoffs between analysis speed and precision. Furthermore, some domains are a better match for certain kinds of code than others. ... | 2006-01-01 |
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