24,038 research outputs found
Looking at Vector Space and Language Models for IR using Density Matrices
In this work, we conduct a joint analysis of both Vector Space and Language
Models for IR using the mathematical framework of Quantum Theory. We shed light
on how both models allocate the space of density matrices. A density matrix is
shown to be a general representational tool capable of leveraging capabilities
of both VSM and LM representations thus paving the way for a new generation of
retrieval models. We analyze the possible implications suggested by our
findings.Comment: In Proceedings of Quantum Interaction 201
Phase retrieval from low-rate samples
The paper considers the phase retrieval problem in N-dimensional complex
vector spaces. It provides two sets of deterministic measurement vectors which
guarantee signal recovery for all signals, excluding only a specific subspace
and a union of subspaces, respectively. A stable analytic reconstruction
procedure of low complexity is given. Additionally it is proven that signal
recovery from these measurements can be solved exactly via a semidefinite
program. A practical implementation with 4 deterministic diffraction patterns
is provided and some numerical experiments with noisy measurements complement
the analytic approach.Comment: Preprint accepted for publication in Sampling Theory in Signal and
Image Processing -- Special issue on SampTa 201
Semantic Retrieval and Automatic Annotation: Linear Transformations, Correlation and Semantic Spaces
This paper proposes a new technique for auto-annotation and semantic retrieval based upon the idea of linearly mapping an image feature space to a keyword space. The new technique is compared to several related techniques, and a number of salient points about each of the techniques are discussed and contrasted. The paper also discusses how these techniques might actually scale to a real-world retrieval problem, and demonstrates this though a case study of a semantic retrieval technique being used on a real-world data-set (with a mix of annotated and unannotated images) from a picture library
Interactive retrieval of video using pre-computed shot-shot similarities
A probabilistic framework for content-based interactive video retrieval is described. The developed indexing of video fragments originates from the probability of the user's positive judgment about key-frames of video shots. Initial estimates of the probabilities are obtained from low-level feature representation. Only statistically significant estimates are picked out, the rest are replaced by an appropriate constant allowing efficient access at search time without loss of search quality and leading to improvement in most experiments. With time, these probability estimates are updated from the relevance judgment of users performing searches, resulting in further substantial increases in mean average precision
Phase Transitions in Phase Retrieval
Consider a scenario in which an unknown signal is transformed by a known
linear operator, and then the pointwise absolute value of the unknown output
function is reported. This scenario appears in several applications, and the
goal is to recover the unknown signal -- this is called phase retrieval. Phase
retrieval has been a popular subject of research in the last few years, both in
determining whether complete information is available with a given linear
operator, and in finding efficient and stable phase retrieval algorithms in the
cases where complete information is available. Interestingly, there are a few
ways to measure information completeness, and each way appears to be governed
by a phase transition of sorts. This chapter will survey the state of the art
with some of these phase transitions, and identify a few open problems for
further research.Comment: Book chapter, survey of recent literature, submitted to Excursions in
Harmonic Analysis: The February Fourier Talks at the Norbert Wiener Cente
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