קולוקוויום וסמינרים

כדי להצטרף לרשימת תפוצה של קולוקוויום מדעי המחשב, אנא בקר בדף מנויים של הרשימה.

קולוקוויום וסמינרים בקרוב

  • CGGC Seminar: Designing N-PolyVector Fields with Complex Polynomials

    דובר:
    אמיר וקסמן (אונ' וינה)
    תאריך:
    יום ראשון, 8.3.2015, 13:30
    מקום:
    חדר 337, בניין טאוב למדעי המחשב

    N-PolyVector fields are introduced, which are a generalization of N-RoSy fields for which the vectors are neither necessarily orthogonal nor rotationally symmetric. A novel representation for N-PolyVectors as the root sets of complex polynomials is given, in addition to the analysis of their topological and geometric properties. A smooth N-PolyVector field can be efficiently generated by solving a sparse linear system without integer variables. This flexibility of N-PolyVector fields can be explored for the design of conjugate vector fields, offering an intuitive tool to generate planar quadrilateral meshes. Further extensions to curl-free fields and other applications will be discussed.

  • Online Learning and Competitive Analysis: a Unified Approach

    דובר:
    שחר חן, הרצאה סמינריונית לדוקטורט
    תאריך:
    יום שלישי, 10.3.2015, 12:30
    מקום:
    טאוב 601
    מנחה:
    Prof. Seffi Naor and Dr. Niv Buchbinder

    Online learning and competitive analysis are two widely studied frameworks for online decision-making settings. Despite the frequent similarity of the problems they study, there are significant differences in their assumptions, goals and techniques, hindering a unified analysis and richer interplay between the two. In this research we provide several contributions in this direction. First, we provide a single unified algorithm which by parameter tuning, interpolates between optimal regret for learning from experts (in online learning) and optimal competitive ratio for the metrical task systems problem (MTS) (in competitive analysis), improving on the results of Blum and Burch (1997). The algorithm also allows us to obtain new regret bounds against "drifting" experts, which might be of independent interest. Moreover, our approach allows us to go beyond experts/MTS, obtaining similar unifying results for structured action sets and "combinatorial experts", whenever the setting has a certain matroid structure. A complementary direction of our research tries to "borrow" various learning techniques, specifically focusing on the online convex optimization domain, in order to obtain new results in the competitive analysis framework. We show how \emph{regularization}, a fundamental method in machine learning and particularly in the field of online learning, can be applied to obtain new results in the area of competitive analysis. We also show how \emph{convex conjugacy} and \emph{Fenchel duality}, other powerful techniques used in online convex optimization and learning, can be used in the competitive analysis setting, allowing us to cope with a richer world of online optimization problems.

  • CGGC Seminar: Persistent Homology

    דובר:
    אלכסנדר ג'רבטיאן (מדעי המחשב, טכניון)
    תאריך:
    יום ראשון, 22.3.2015, 13:30
    מקום:
    חדר 337, בניין טאוב למדעי המחשב

    Shapes are usually described by their geometrical characteristics. Obviously, a rabbit doesn't look like a horse, because of its curvature for instance. However, some characteristics of a shape are independent of its geometry. A rugby ball is still a ball, and a doughnut looks like a tire. Those are called topological features of the shape, and homology is one the tool that mathematicians use to separate a sphere from a torus. A rabbit being equivalent to a horse, this often makes topology be a neglected tool in computer science for obvious reasons. However, some topological knowledge can sometimes help us have a better understanding of the underlying shape, behind the geometry, and then help make meaningful topological simplification. In this talk, I will introduce the concept and the algorithm of persistent homology, a tool to classify the importance of the topological features of arbitrary shapes. We will for instance count the number of mountains and valleys in a given geography, and sort them by topological importance.

  • ceClub: Deep learning with NVIDIA GPUs

    דובר:
    ג'ונתן כהן (IVIDIA)
    תאריך:
    יום חמישי, 26.3.2015, 13:30
    מקום:
    טאוב 6

    NVIDIA GPUs are powering a revolution in machine learning. With the rise of deep learning algorithms, in particular deep convolutional neural networks, computers are learning to see, hear, and understand the world around us in ways never before possible. Image recognition and detection systems are getting close to and in some cases surpassing human-level performance. I will talk about deep learning in the context of several new NVIDIA initiatives ranging from hardware platforms, software tools and libraries, and our recently announced DRIVE PX module for autonomous driving.

    Bio:
    Jonathan Cohen is Director of Engineering for NVIDIA's GPU-accelerated deep learning software platform. Before moving to the product side of NVIDIA, Mr. Cohen spent three years as a senior research scientist with NVIDIA Research developing scientific computing and real-time physical simulation applications on NVIDIA's massively parallel GPUs.

  • אירוע בוגרי תארים מתקדמים במדעי המחשב

    אירוע בוגרי תארים מתקדמים במדעי המחשב

    תאריך:
    יום חמישי, 2.4.2015, 14:30
    מקום:
    בניין טאוב למדעי המחשב

    אנו שמחים להזמינכם לאירוע בוגרי תארים מתקדמים במדעי המחשב אשר יתקיים ביום חמישי, 2 באפריל, 2015 בבניין טאוב למדעי המחשב. פרטים נוספים בכרזה המצורפת והזמנה תישלח בקרוב.

    כדי להבטיח את השתתפות כל הבוגרים, נשמח לקבל מכם שמות ופרטי קשר של בוגרים מבין מכריכם.

    מקווים לראותכם.