TY - CONF
AB - Many computer vision problems have an asymmetric distribution of information between training and test time. In this work, we study the case where we are given additional information about the training data, which however will not be available at test time. This situation is called learning using privileged information (LUPI). We introduce two maximum-margin techniques that are able to make use of this additional source of information, and we show that the framework is applicable to several scenarios that have been studied in computer vision before. Experiments with attributes, bounding boxes, image tags and rationales as additional information in object classification show promising results.
AU - Sharmanska, Viktoriia
AU - Quadrianto, Novi
AU - Lampert, Christoph
ID - 2293
TI - Learning to rank using privileged information
ER -
TY - CONF
AB - In this work we propose a system for automatic classification of Drosophila embryos into developmental stages.
While the system is designed to solve an actual problem in biological research, we believe that the principle underly-
ing it is interesting not only for biologists, but also for researchers in computer vision. The main idea is to combine two orthogonal sources of information: one is a classifier trained on strongly invariant features, which makes it applicable to images of very different conditions, but also leads to rather noisy predictions. The other is a label propagation step based on a more powerful similarity measure that however is only consistent within specific subsets of the data at a time.
In our biological setup, the information sources are the shape and the staining patterns of embryo images. We show
experimentally that while neither of the methods can be used by itself to achieve satisfactory results, their combina-
tion achieves prediction quality comparable to human performance.
AU - Kazmar, Tomas
AU - Kvon, Evgeny
AU - Stark, Alexander
AU - Lampert, Christoph
ID - 2294
TI - Drosophila Embryo Stage Annotation using Label Propagation
ER -
TY - CONF
AB - We consider partially observable Markov decision processes (POMDPs) with ω-regular conditions specified as parity objectives. The qualitative analysis problem given a POMDP and a parity objective asks whether there is a strategy to ensure that the objective is satisfied with probability 1 (resp. positive probability). While the qualitative analysis problems are known to be undecidable even for very special cases of parity objectives, we establish decidability (with optimal EXPTIME-complete complexity) of the qualitative analysis problems for POMDPs with all parity objectives under finite-memory strategies. We also establish asymptotically optimal (exponential) memory bounds.
AU - Chatterjee, Krishnendu
AU - Chmelik, Martin
AU - Tracol, Mathieu
ID - 2295
TI - What is decidable about partially observable Markov decision processes with omega-regular objectives
VL - 23
ER -
TY - JOUR
AB - We present an overview of mathematical results on the low temperature properties of dilute quantum gases, which have been obtained in the past few years. The presentation includes a discussion of Bose-Einstein condensation, the excitation spectrum for trapped gases and its relation to superfluidity, as well as the appearance of quantized vortices in rotating systems. All these properties are intensely being studied in current experiments on cold atomic gases. We will give a description of the mathematics involved in understanding these phenomena, starting from the underlying many-body Schrödinger equation.
AU - Seiringer, Robert
ID - 2297
IS - 2
JF - Japanese Journal of Mathematics
TI - Hot topics in cold gases: A mathematical physics perspective
VL - 8
ER -
TY - CONF
AB - We present a shape analysis for programs that manipulate overlaid data structures which share sets of objects. The abstract domain contains Separation Logic formulas that (1) combine a per-object separating conjunction with a per-field separating conjunction and (2) constrain a set of variables interpreted as sets of objects. The definition of the abstract domain operators is based on a notion of homomorphism between formulas, viewed as graphs, used recently to define optimal decision procedures for fragments of the Separation Logic. Based on a Frame Rule that supports the two versions of the separating conjunction, the analysis is able to reason in a modular manner about non-overlaid data structures and then, compose information only at a few program points, e.g., procedure returns. We have implemented this analysis in a prototype tool and applied it on several interesting case studies that manipulate overlaid and nested linked lists.
AU - Dragoi, Cezara
AU - Enea, Constantin
AU - Sighireanu, Mihaela
ID - 2298
TI - Local shape analysis for overlaid data structures
VL - 7935
ER -