Roy Schwartz: "Advances in Traffic Engineering and Discrepancy"
I will discuss two recent works:
- Long running transfers in wide area networks are usually time critical, as delays might impact service quality, affect customer revenue, and increase costs incurred by waste of resources. Current traffic engineering systems fall short as they do not provide pre-facto guarantees on such long running transfers. I will present an online traffic engineering system that provides pre-facto guarantees while maximizing both fairness and network utility. The system is based on theoretical algorithmic techniques for solving packing and covering linear programs, and can quickly handle an evolving linear program containing up to millions of variables and constraints.
- Combinatorial discrepancy is a basic problem in computer science and combinatorics, that has applications in diverse areas such as: computational geometry, complexity theory, Monte-Carlo simulation, number theory and more. Given a family of subsets $S_1,\ldots,S_n$ of a universe $N$ of size $n$, the goal is to color the elements of $N$ by one of two colors $\{-1,+1\}$ such that each set is colored as evenly as possible. Spencer's well known theorem asserts that this can be done while keeping the absolute value of the sum of the colors of every set to be $O(\sqrt{n})$. Known proofs, algorithmic and existential, recursively construct "partial colorings", which assign colors only to half the universe $N$. Unfortunately, this approach fails to provide tight guarantees to other important discrepancy problem, e.g., the Beck-Fiala and Koml\'os conjectures. Therefore, it has been an open question to find new techniques that avoid partial colorings. In this work I will present the first algorithm that directly computes a full coloring. The algorithm is based on a geometric perspective and in its core is the analysis of ellipsoids contained in polytopes.
Jonathan Berant: "Scalable algorithms for translating natural language to logical form"
Conversational interfaces and virtual assistants such as Apple's Siri, Google Now, and Facebook Graph Search, have led to a rising interest in systems that can translate natural language commands and questions to formal logical forms (like SQL queries) that can be executed against a knowledge base. A major challenge has been to scale these systems, known as semantic parsers, to large knowledge bases. In this talk, I will describe novel algorithms for large scale semantic parsing.
Sigal Oren: "An Algorithmic Approach for Analyzing Social Phenomena"
These days, as more and more people use online applications such as Wikipedia, Stack Overflow or Facebook, social phenomena that originally appeared in the offline world make an appearance online and new social phenomena emerge. This calls for narrowing the gap between computer science and social sciences in general, and sociology in particular. The opportunity here is twofold. First, the algorithmic approach can offer a new perspective on social phenomena previously studied in social sciences.
Natalia Silberstein: "Coding for Distributed Storage Systems"
In distributed storage systems (DSS) data is stored over a large number of storage nodes in such a way that a user can always retrieve the stored data, even if some storage nodes fail. To achieve such resilience against node failures, DSS introduce data redundancy based on different coding techniques. When a single node fails, the system performs node repair, i.e., reconstructs the data stored in the failed node in order to maintain the required level of redundancy.
Michael Bronstein: "New old ways for dealing with geometric data"
In recent years, geometric data is gaining increasing interest both in the academia and industry. In computer graphics and vision, this interest is owed to the rapid development of 3D acquisition and printing technologies, as well as the explosive growth of publicly-available 3D shape repositories. In machine learning, there is a gradual understanding that geometric structure plays an important role in high-dimensional complicated datasets.
Oren Zuckerman: "Internet of Things & Assistive technologies—research projects at the IDC Media Innovation Lab"
The Media Innovation Lab at IDC is a research and prototyping lab, focused on the interaction between people and technology in domains that merge between the physical and digital worlds. Dr. Oren Zuckerman will present the "Objects for Change" research projects at the media innovation lab, including research opportunities for CS students.
Tal Hassner: "Viewing Expressive Real-World Faces in 3D"
We present a data-driven method for estimating the 3D shapes of faces viewed in single, unconstrained photos. Our method was designed with an emphasis on robustness and efficiency—with the explicit goal of deployment in real-world applications which reconstruct and display faces in 3D. Our key observation is that for many practical applications, warping the shape of a reference face to match the appearance of a query is enough to produce realistic impressions of the query’s 3D shape.
Goren Gordon: "Biological and artificial curiosity: models, behaviors and robots"
Curiosity is one of the major human drives. Can we model curiosity in biological agents? Can we implement them in artificial systems? What happens when a curious child meets a curious robot? In this talk I present recent work on the study of curiosity. First, studies of curiosity-driven behaviors in humans and rodents are presented, where we show that biological agents attempt to manage their novelty in a structured manner. A model that captures this structure is presented, wherein emergent exploration behaviors are balanced with novelty-based withdrawal-like actions.
Antigoni Polychroniadou: "Cold Boot Attacks - Recovering Noisy RSA Keys"
Cold boot attacks are a class of attacks wherein memory remanence eff?ects are exploited to extract data from a computer's memory. The idea is that modern computer memories retain data for periods of time after power is removed, so an attacker with physical access to a machine may be able to recover, for example, cryptographic key information. The time during which data is retained can be increased by cooling the memory chips. However, because the memory gradually degrades over time once power is removed, only a noisy version of the data may be recoverable.
Boaz Ben-Moshe: "Geometric Methods for Accurate Indoor Navigation"
This talk covers positioning & navigation challenges. We first give an introduction on GNSS (e.g. GPS) and focus on cases where GPS navigation is not sufficient (i.e., Indoor, or urban canyons). Then a short survey on “smartphone-sensors” will be given and few sub-problems on sensor fusion will be presented. The main part of the talk will cover a new geometric (bio-inspired) framework for navigation and mapping using off-the-shelf mobile devices followed by few positioning simulation and an actual demonstration.