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Carl Staelin

Carl Staelin

Carl Staelin works for Google and is assistant editor for the Journal of Electronic Imaging. He was Chief Technologist for HP Labs Israel, working on digital commercial print, automatic image analysis and enhancement, and enterprise IT management. His research interests include storage systems, machine learning, image analysis and processing, document and information management, and performance analysis. He received his PhD in Computer Science from Princeton University in 1991 in high performance file system design.

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    Models for Neural Spike Computation and Cognition
    David H. Staelin
    CreateSpace, Seattle, WA (2011), pp. 142
    Preview abstract This monograph addresses the intertwined mathematical, neurological, and cognitive mysteries of the brain. It first evaluates the mathematical performance limits of simple spiking neuron models that both learn and later recognize complex spike excitation patterns in less than one second without using training signals unique to each pattern. Simulations validate these models, while theoretical expressions validate their simpler performance parameters. These single-neuron models are then qualitatively related to the training and performance of multi-layer neural networks that may have significant feedback. The advantages of feedback are then qualitatively explained and related to a model for cognition. This model is then compared to observed mild hallucinations that arguably include accelerated time-reversed video memories. The learning mechanism for these binary threshold-firing “cognon” neurons is spike-timing-dependent plasticity (STDP) that depends only on whether the spike excitation pattern presented to a given single “learning-ready” neuron within a period of milliseconds causes that neuron to fire or “spike”. The “false-alarm” probability that a trained neuron will fire for a random unlearned pattern can be made almost arbitrarily low by reducing the number of patterns learned by each neuron. Models that use and that do not use spike timing within patterns are evaluated. A Shannon mutual information metric (recoverable bits/neuron) is derived for binary neuron models that are characterized only by their probability of learning a random input excitation pattern presented to that neuron during learning readiness, and by their false-alarm probability for random unlearned patterns. Based on simulations, the upper bounds to recoverable information are ~0.1 bits per neuron for optimized neuron parameters and training. This information metric assumes that: 1) each neural spike indicates only that the responsible neuron input excitation pattern (a pattern lasts less than the time between consecutive patterns, say 30 milliseconds) had probably been seen earlier while that neuron was “learning ready”, and 2) information is stored in the binary synapse strengths. This focus on recallable learned information differs from most prior metrics such as pattern classification performance and metrics relying on pattern-specific training signals other than the normal input spikes. This metric also shows that neuron models can recall useful Shannon information only if their probability of firing randomly is lowered between learning and recall. Also discussed are: 1) how rich feedback might permit improved noise immunity, learning and recognition of pattern sequences, compression of data, associative or content-addressable memory, and development of communications links through white matter, 2) extensions of cognon models that use spike timing, dendrite compartments, and new learning mechanisms in addition to spike timing- dependent plasticity (STDP), 3) simulations that show how simple optimized neuron models can have optimum numbers of binary synapses in the range between 200 and 10,000, depending on neural parameters, and 4) simulation results for parameters like the average bits/spike, bits/neuron/second, maximum number of learnable patterns, optimum ratios between the strengths of weak and strong synapses, and probabilities of false alarms. View details
    Clustered-Dot Halftoning With Direct Binary Search
    P. Goyal
    M. Gupta
    M. Fischer
    O. Shacham
    J.P. Allebach
    IEEE Transactions on Image Processing, vol. 22 (2013), pp. 473-487
    ICC Profile Extension for Device MTF Characterization
    Lior Shapira
    Ron Banner
    Proceedings NIP & Digital Fabrication Conference, 2011 International Conference on Digital Printing Technologies, pp. 24-28
    Electro-photographic model based stochastic clustered-dot halftoning with direct binary search
    P. Goyal
    M. Gupta
    M. Fischer
    O. Shacham
    T. Kashti
    J. Allebach
    Image Processing (ICIP), 2011 18th IEEE International Conference on, pp. 1721-1724
    Automatic visual inspection and defect detection on variable data prints
    Marie Vans
    Sagi Schein
    Pavel Kisilev
    Steve Simske
    Ram Dagan
    Shlomo Harush
    Journal of Electronic Imaging, vol. 20 (2011)
    Cost function analysis for stochastic clustered-dot halftoning based on direct binary search
    Puneet Goyal
    Madhur Gupta
    Mani Fischer
    Omri Shacham
    Jan Allebach
    Proc. SPIE 7866, Color Imaging XVI: Displaying, Processing, Hardcopy, and Applications, Society of Photo-Optical Instrumentation Engineers (SPIE) (2011)
    CSched: Real-time disk scheduling with concurrent I/O requests
    Gidi Amir
    David Ben-Ovadia
    Ram Dagan
    Michael Melamed
    Dave Staas
    Hewlett-Packard Laboratories (2011)
    Design of color screen sets for robustness to color plane misregistration
    Jin-Young Kim
    Yung-Yao Chen
    M. Fischer
    O. Shacham
    J.P. Allebach
    18th IEEE International Conference on Image Processing (ICIP) (2011), pp. 1733-1736
    Design of color screen tile vector sets
    Jin-Young Kim
    Yung-Yao Chen
    Mani Fischer
    Omri Shacham
    Kurt Bengston
    Jan Allebach
    Proc. SPIE 7866, Color Imaging XVI: Displaying, Processing, Hardcopy, and Applications, 78661C, Society of Photo-Optical Instrumentation Engineers (SPIE) (2011)
    Local Gray Component Replacement Using Image Analysis
    Pavel Kisilev
    Yohanan Sivan
    Michal Aharon
    Renato Keshet
    Gregory Braverman
    Shlomo Harush
    19th Color and Imaging Conference Final Program and Proceedings, Society for Imaging Science and Technology (2011), pp. 234-238
    Detecting and exploiting near-sortedness for efficient relational query evaluation
    Sagi Ben-Moshe
    Yaron Kanza
    Eldar Fischer
    Arie Matsliah
    Mani Fischer
    Proceedings of the 14th International Conference on Database Theory, ACM, New York, NY, USA (2011), pp. 256-267
    Creating the knowledge about IT events
    Gilad Barash
    Ira Cohen
    Eli Mordechai
    Rafael Dakar
    Proceedings of the 2010 workshop on Managing systems via log analysis and machine learning techniques, USENIX Association, Berkeley, CA, USA, pp. 1-1
    Memory hierarchy performance measurement of commercial dual-core desktop processors
    Lu Peng
    Jih-Kwon Peir
    Tribuvan K. Prakash
    Yen-Kuang Chen
    David M. Koppelman
    Journal of Systems Architecture - Embedded Systems Design, vol. 54 (2008), pp. 816-828
    PDF document restoration and optimization during image enhancement
    Hui Chao
    Sagi Schein
    Marie Vans
    John Lumley
    Proceedings of the eighth ACM symposium on Document engineering, ACM, New York, NY, USA (2008), pp. 150-153
    Biblio: automatic meta-data extraction
    Michael Elad
    Darryl Greig
    Oded Shmueli
    Marie Vans
    IJDAR, vol. 10 (2007), pp. 113-126
    lmbench: an extensible micro-benchmark suite
    Softw., Pract. Exper., vol. 35 (2005), pp. 1079-1105
    mkpkg: A software packaging tool
    LISA (1998), pp. 243-252
    mhz: Anatomy of a micro-benchmark
    Larry McVoy
    USENIX Annual Technical Conference, USENIX, Berkeley, CA (1998)
    The HP AutoRAID hierarchical storage system
    Richard Golding
    Tim Sullivan
    ACM Transactions on Computer Systems (TOCS), vol. 14 (1996), pp. 108-136
    lmbench: Portable tools for performance analysis
    Larry McVoy
    USENIX Annual Technical Conference, USENIX, Berkeley, CA (1996), pp. 279-274
    Mariposa: A Wide-Area Distributed Database System
    Michael Stonebraker
    Paul M. Aoki
    Witold Litwin
    Avi Pfeffer
    Adam Sah
    Jeff Sidell
    Andrew Yu
    VLDB J., vol. 5 (1996), pp. 48-63
    Data Replication in Mariposa
    Jeff Sidell
    Paul M. Aoki
    Adam Sah
    Michael Stonebraker
    Andrew Yu
    ICDE (1996), pp. 485-494
    The HP AutoRAID hierarchical storage system
    J. Wilkes
    R. Golding
    T. Sullivan
    SIGOPS Oper. Syst. Rev., vol. 29 (1995), pp. 96-108
    Idleness is not sloth
    Richard A. Golding
    Peter Bosch II
    Tim Sullivan
    USENIX Winter (1995), pp. 201-212
    An Economic Paradigm for Query Processing and Data Migration in Mariposa
    Michael Stonebraker
    Robert Devine
    Marcel Kornacker
    Witold Litwin
    Avi Pfeffer
    Adam Sah
    PDIS (1994), pp. 58-67
    HighLight: Using a Log-structured File System for Tertiary Storage Management
    John T. Kohl
    Michael Stonebraker
    USENIX Winter (1993), pp. 435-448
    An Implementation of a Log-Structured File System for UNIX
    Margo I. Seltzer
    Keith Bostic
    Marshall K. McKusick
    USENIX Winter (1993), pp. 307-326
    HighLight: a file system for tertiary storage
    J. Kohl
    M. Stonebraker
    Mass Storage Systems, 1993. Putting all that Data to Work. Proceedings., Twelfth IEEE Symposium on, pp. 157-161
    DataMesh parallel storage servers
    Chia Chao
    Robert English
    David Jacobson
    Bart Sears
    Alex Stepanov
    SIGOPS Oper. Syst. Rev., vol. 26 (1992), pp. 11
    Smart Filesystems
    Hector Garcia-Molina
    USENIX Winter (1991), pp. 45-52
    File system design using large memories
    H. Garcia-Molina
    Information Technology, 1990. 'Next Decade in Information Technology', Proceedings of the 5th Jerusalem Conference on (Cat. No.90TH0326-9), pp. 11-21
    Data Management with Massive Memory: A Summary
    Hector Garcia-Molina
    Robert K. Abbott
    Chris Clifton
    Kenneth Salem
    PRISMA Workshop (1990), pp. 63-70
    Evaluation ot Monitor Complexity for Concurrently Testing Microprogrammed Control Units
    Alexander Albicki
    ITC (1985), pp. 733-736