A Tutorial on Spectral Clustering - People | MIT CSAIL

Speculative Buffer Overflows: Attacks and Defenses

Speculative Buffer Overflows: Attacks and Defenses Vladimir Kiriansky vlk@csail.mit.edu Carl Waldspurger carl@waldspurger.org Abstract Practical attacks that exploit speculative execution can leak

  Attacks

Introduction To Machine Learning - people.csail.mit.edu

Introduction To Machine Learning David Sontag New York University Lecture 21, April 14, 2016 David Sontag (NYU) Introduction To Machine Learning Lecture 21, April 14, 2016 1 / 14. Expectation maximization Algorithm is as follows: 1 Write down the complete log-likelihood log p(x;z; ) in such a way

  Introduction, Machine, Learning, Introduction to machine learning

Computational Imaging: The Race Against Time

The Race Against Time Computational Imaging: The Race Against Time Paul Debevec USC Institute for Creative Technologies USC Viterbi School of Engineering 2005 Symposium on Computational Photography and Video

  Computational, Time, Atingsa, Care, Imaging, Computational imaging, The race against time, Race against time computational imaging

Vantage: Scalable and Efficient Fine-Grain Cache Partitioning

Vantage is derived from analytical models, which allow us to provide strong guarantees and bounds on associativity and siz- ing independent of the number of partitions and their behaviors.

  Fine, Grain, Partitioning, Vantage, Scalable, Cache, Efficient, Scalable and efficient fine grain cache partitioning

Object detection and localization using local and global ...

Object detection and localization using local and global features 5 * = P f g Fig.3. Creating a random dictionary entry consisting of a filter f, patch P and Gaussian mask g. Dotted blue is the annotated bounding box, dashed green is the chosen patch.

  Using, Local, Object, Detection, Localization, Object detection and localization using local

Jade: A High-Level, Machine-Independent Language for ...

Jade: A High-Level, Machine-Independent Language for Parallel Programming Martin C. Rinard, Daniel J. Scales and Monica S. Lam Computer Systems Laboratory Stanford University, CA 94305 1 Introduction The past decade has seen tremendous progress in computer architecture and a …

  Programming, Language, Machine, Independent, Parallel, Jade, Machine independent language for parallel programming

A secure processor architecture for encrypted computation ...

Ascend is marginally more complex than a conventional proces- sor, in the sense that Ascend must implement an ISA and also make sure that the work it does is sufficiently obfuscated.

  Processor, Architecture, Secure, Computation, Ascend, Encrypted, Secure processor architecture for encrypted computation

Bluetooth for Programmers

Because Bluetooth programming shares much in common with network programming, there will be frequent references and comparisons to concepts in network programming such as sockets and the TCP/IP transport protocols.

  Programming, Programmer, Bluetooth, Bluetooth for programmers

Jigsaw: Scalable Software-Defined Caches

caching that Jigsaw builds and improves on: techniques to partition a shared cache, and non-uniform cache architectures. Table 1 summarizes the main differences among techniques.

  Software, Scalable, Cache, Jigsaw, Defined, Scalable software defined caches

JIGSAW - Massachusetts Institute of Technology

Jigsaw is the only scheme to simultaneously benefit network and DRAM latency Optimum . Evaluation: Energy 60 ! 16-core multiprogrammed mixes ! McPAT models of full-system energy (chip + DRAM) ! Jigsaw achieves best energy reduction ! Up to 72%, gmean of 11% ! …

  Jigsaw

I, Robot

She obtained her bachelor’s degree at Columbia in 2003 and began graduate work in cybernetics. All that had been done in the mid-twentieth century on “calculating machines” had been upset by Robertson and his positronic brain-paths. The miles of relays and photocells had given way to the

  Cybernetics

Automated Segmentation and Morphometry of Cell and …

and analysis developed by Media Cybernetics, USA. Among its advanced capabilities can be counted image fusion, extended depth of view, object tracking, thresholding of color images and morphological segmentation. Its functionality closely matches the one developed in ImageJ.

  Segmentation, Cybernetics, Imagej

BASIC CONCEPTS OF LOGIC - UMass

cybernetics. Even if these empirical disciplines were considerably more advanced than they presently are, the most they could disclose is the exact process that goes on in a being's head when he or she (or it) is reasoning. They could not, however, tell us whether the being is reasoning correctly or incorrectly.

  Logic, Cybernetics

Cybernetics and Second-Order Cybernetics

Cybernetics is the science that studies the abstract principles of organization in complex systems. It is concerned not so much with what systems consist of, but how they function. Cybernetics focuses on how systems use information, models, and control actions to steer towards and maintain their goals, while counteracting various disturbances.

  Second, Order, Second order cybernetics, Cybernetics

Pattern Recognition and Machine Learning

Preface Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of