1,475 research outputs found
Optical Flow Requires Multiple Strategies (but only one network)
We show that the matching problem that underlies optical flow requires
multiple strategies, depending on the amount of image motion and other factors.
We then study the implications of this observation on training a deep neural
network for representing image patches in the context of descriptor based
optical flow. We propose a metric learning method, which selects suitable
negative samples based on the nature of the true match. This type of training
produces a network that displays multiple strategies depending on the input and
leads to state of the art results on the KITTI 2012 and KITTI 2015 optical flow
benchmarks
Low-Sensitivity Functions from Unambiguous Certificates
We provide new query complexity separations against sensitivity for total
Boolean functions: a power separation between deterministic (and even
randomized or quantum) query complexity and sensitivity, and a power
separation between certificate complexity and sensitivity. We get these
separations by using a new connection between sensitivity and a seemingly
unrelated measure called one-sided unambiguous certificate complexity
(). We also show that is lower-bounded by fractional block
sensitivity, which means we cannot use these techniques to get a
super-quadratic separation between and . We also provide a
quadratic separation between the tree-sensitivity and decision tree complexity
of Boolean functions, disproving a conjecture of Gopalan, Servedio, Tal, and
Wigderson (CCC 2016).
Along the way, we give a power separation between certificate
complexity and one-sided unambiguous certificate complexity, improving the
power separation due to G\"o\"os (FOCS 2015). As a consequence, we
obtain an improved lower-bound on the
co-nondeterministic communication complexity of the Clique vs. Independent Set
problem.Comment: 25 pages. This version expands the results and adds Pooya Hatami and
Avishay Tal as author
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Jacqueline Kahanoff and the demise of the Levantine
More than anything else, Jacqueline Kahanoff is associated with the term Levantinism and, more specifically, with turning the term, which for many years had a derogatory meaning, into a positive source of identity. However, this reading of Kahanoff – namely, a carrier of the message of Levantinism as a bridge between Orient and Occident – seems to tell us more about Kahanoff’s readers than about Kahanoff herself. A careful reading of her writings reveals a different Kahanoff, a person who, more than being the originator and proponent of a new kind of identity, while moving swiftly across cultures and feeling at home nowhere because her home was everywhere, was actually well entrenched in the west, in Zionism and in Israel
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Uncertainty Quantification in Composite Materials
The random nature of the micro-structural attributes in materials in general and composite material systems in particular requires expansion of material modeling in a way that will incorporate their inherent uncertainty and predict its impact on material properties and mechanical response in multiple scales. Despite the importance of capturing and modeling material randomness, there are numerous challenges in structural characterization that are yet to be addressed.
The work presented in this essay takes a few steps towards an improved material modeling approach which encompasses structural randomness in order to produce a more realistic representation of material systems. For this end a computational framework was developed to generate a realistic representative volume element which reflects the inherent structural randomness. First stochastic structural elements were identified and registered from imaging data and parameters were assigned to represent those elements. Statistical characterization of the random attributes was followed by the construction of a representative volume element which shared the same structural statistical characteristics with the original material system. The resultant statistical equivalent representative volume element (SERVE) was then used in finite element simulations which provided homogenized properties and mechanical response predictions. The suggested framework was developed and then implemented on 3 different material systems.
Image processing and analysis in one of the material systems extended the original scope of this work to solving a machine vision and learning problem. Object segmentation for the purpose object and pattern recognition has been a long standing subject of interest in the field of machine vision. Despite the significant attention given to the development of segmentation and recognition methods, the critical challenge of separating merged objects did not share the spotlight. A simple yet original approach to overcome this hurdle was developed using unsupervised classification and separation of objects in 3D. Lower dimensionality classifiers were joined to provide a powerful higher dimensionality classification tool. The robustness of this approach is illustrated through its implementation on two case studies of merged objects. Applications of this methodology can further extend from structural classification to general problems of clustering and classification in various fields
Phonological (un)certainty weights lexical activation
Spoken word recognition involves at least two basic computations. First is
matching acoustic input to phonological categories (e.g. /b/, /p/, /d/). Second
is activating words consistent with those phonological categories. Here we test
the hypothesis that the listener's probability distribution over lexical items
is weighted by the outcome of both computations: uncertainty about phonological
discretisation and the frequency of the selected word(s). To test this, we
record neural responses in auditory cortex using magnetoencephalography, and
model this activity as a function of the size and relative activation of
lexical candidates. Our findings indicate that towards the beginning of a word,
the processing system indeed weights lexical candidates by both phonological
certainty and lexical frequency; however, later into the word, activation is
weighted by frequency alone.Comment: 6 pages, 4 figures, accepted at: Cognitive Modeling and Computational
Linguistics (CMCL) 201
Dynamical evolution of the young stars in the Galactic center
Recent observations of the Galactic center revealed a nuclear disk of young
OB stars near the massive black hole (MBH), in addition to many similar
outlying stars with higher eccentricities and/or high inclinations relative to
the disk (some of them possibly belonging to a second disk). In addition,
observations show the existence of young B stars (the 'S-cluster') in an
isotropic distribution in the close vicinity of the MBH ( pc). We use
extended N-body simulations to probe the dynamical evolution of these two
populations. We show that the stellar disk could have evolved to its currently
observed state from a thin disk of stars formed in a gaseous disk, and that the
dominant component in its evolution is the interaction with stars in the cusp
around the MBH. We also show that the currently observed distribution of the
S-stars could be consistent with a capture origin through 3-body binary-MBH
interactions. In this scenario the stars are captured at highly eccentric
orbits, but scattering by stellar black holes could change their eccentricity
distribution to be consistent with current observations.Comment: 5 pages, 2 figures. To appear in the proceedings of the Central
Kiloparsec conference, 2008, Cret
The effectiveness of hedging foreign exchange rate risk: an emerging market perspective
Thesis (M.M. (Finance & Investment))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Graduate School of Business Administration, 2013.This study provides an analysis of the effectiveness of the foreign currency hedging abilities
afforded by the futures market. The focus is on the currencies of six emerging markets,
namely; Brazil, India, Mexico, Russia, South Africa and Turkey. By examining emerging
market currencies we can examine the effect that possible mispricing and lack of liquidity can
have on hedging effectiveness. To this effect, this article uses the regression method, as
allowed by the accounting standard FAS 133, to assess the effectiveness of futures contracts
as a hedging mechanism for emerging market currencies. The methods follow previous
studies such as Hill and Schneeweis (1982) which consider the length of the hedging horizon
and time to expiration due to their effect on hedge effectiveness. Results indicate consistent
hedge effectiveness in only South Africa and Turkey, with reasonable hedge effectiveness
exhibited by Mexico and Russia. Sensible explanations are given for the extreme hedge
ineffectiveness that can be seen in the Brazilian and Indian tests
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