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9,400 | Incorporating Prior Information in Compressive Online Robust Principal
Component Analysis | cs.IT | We consider an online version of the robust Principle Component Analysis
(PCA), which arises naturally in time-varying source separations such as video
foreground-background separation. This paper proposes a compressive online
robust PCA with prior information for recursively separating a sequences of
frames into spars... | computer science |
9,401 | Dynamic time warping distance for message propagation classification in
Twitter | cs.AI | Social messages classification is a research domain that has attracted the
attention of many researchers in these last years. Indeed, the social message
is different from ordinary text because it has some special characteristics
like its shortness. Then the development of new approaches for the processing
of the social... | computer science |
9,402 | The Causal Frame Problem: An Algorithmic Perspective | cs.AI | The Frame Problem (FP) is a puzzle in philosophy of mind and epistemology,
articulated by the Stanford Encyclopedia of Philosophy as follows: "How do we
account for our apparent ability to make decisions on the basis only of what is
relevant to an ongoing situation without having explicitly to consider all that
is not ... | computer science |
9,403 | Entropic Causality and Greedy Minimum Entropy Coupling | cs.IT | We study the problem of identifying the causal relationship between two
discrete random variables from observational data. We recently proposed a novel
framework called entropic causality that works in a very general functional
model but makes the assumption that the unobserved exogenous variable has small
entropy in t... | computer science |
9,404 | A Study of FOSS'2013 Survey Data Using Clustering Techniques | cs.AI | FOSS is an acronym for Free and Open Source Software. The FOSS 2013 survey
primarily targets FOSS contributors and relevant anonymized dataset is publicly
available under CC by SA license. In this study, the dataset is analyzed from a
critical perspective using statistical and clustering techniques (especially
multiple... | computer science |
9,405 | Learning what matters - Sampling interesting patterns | stat.ML | In the field of exploratory data mining, local structure in data can be
described by patterns and discovered by mining algorithms. Although many
solutions have been proposed to address the redundancy problems in pattern
mining, most of them either provide succinct pattern sets or take the interests
of the user into acc... | computer science |
9,406 | Direct Estimation of Information Divergence Using Nearest Neighbor
Ratios | cs.IT | We propose a direct estimation method for R\'{e}nyi and f-divergence measures
based on a new graph theoretical interpretation. Suppose that we are given two
sample sets $X$ and $Y$, respectively with $N$ and $M$ samples, where
$\eta:=M/N$ is a constant value. Considering the $k$-nearest neighbor ($k$-NN)
graph of $Y$ i... | computer science |
9,407 | Towards a Unified Taxonomy of Biclustering Methods | cs.AI | Being an unsupervised machine learning and data mining technique,
biclustering and its multimodal extensions are becoming popular tools for
analysing object-attribute data in different domains. Apart from conventional
clustering techniques, biclustering is searching for homogeneous groups of
objects while keeping their... | computer science |
9,408 | Cost-Optimal Learning of Causal Graphs | cs.AI | We consider the problem of learning a causal graph over a set of variables
with interventions. We study the cost-optimal causal graph learning problem:
For a given skeleton (undirected version of the causal graph), design the set
of interventions with minimum total cost, that can uniquely identify any causal
graph with... | computer science |
9,409 | FairJudge: Trustworthy User Prediction in Rating Platforms | cs.SI | Rating platforms enable large-scale collection of user opinion about items
(products, other users, etc.). However, many untrustworthy users give
fraudulent ratings for excessive monetary gains. In the paper, we present
FairJudge, a system to identify such fraudulent users. We propose three
metrics: (i) the fairness of ... | computer science |
9,410 | Robust Causal Estimation in the Large-Sample Limit without Strict
Faithfulness | stat.ML | Causal effect estimation from observational data is an important and much
studied research topic. The instrumental variable (IV) and local causal
discovery (LCD) patterns are canonical examples of settings where a closed-form
expression exists for the causal effect of one variable on another, given the
presence of a th... | computer science |
9,411 | Graphical Models: An Extension to Random Graphs, Trees, and Other
Objects | stat.ML | In this work, we consider an extension of graphical models to random graphs,
trees, and other objects. To do this, many fundamental concepts for
multivariate random variables (e.g., marginal variables, Gibbs distribution,
Markov properties) must be extended to other mathematical objects; it turns out
that this extensio... | computer science |
9,412 | Morpheo: Traceable Machine Learning on Hidden data | cs.AI | Morpheo is a transparent and secure machine learning platform collecting and
analysing large datasets. It aims at building state-of-the art prediction
models in various fields where data are sensitive. Indeed, it offers strong
privacy of data and algorithm, by preventing anyone to read the data, apart
from the owner an... | computer science |
9,413 | Understanding Negations in Information Processing: Learning from
Replicating Human Behavior | cs.AI | Information systems experience an ever-growing volume of unstructured data,
particularly in the form of textual materials. This represents a rich source of
information from which one can create value for people, organizations and
businesses. For instance, recommender systems can benefit from automatically
understanding... | computer science |
9,414 | Event Stream-Based Process Discovery using Abstract Representations | cs.DB | The aim of process discovery, originating from the area of process mining, is
to discover a process model based on business process execution data. A
majority of process discovery techniques relies on an event log as an input. An
event log is a static source of historical data capturing the execution of a
business proc... | computer science |
9,415 | Active learning machine learns to create new quantum experiments | cs.AI | How useful can machine learning be in a quantum laboratory? Here we raise the
question of the potential of intelligent machines in the context of scientific
research. A major motivation for the present work is the unknown reachability
of various entanglement classes in quantum experiments. We investigate this
question ... | computer science |
9,416 | TIP: Typifying the Interpretability of Procedures | cs.AI | We provide a novel notion of what it means to be interpretable, looking past
the usual association with human understanding. Our key insight is that
interpretability is not an absolute concept and so we define it relative to a
target model, which may or may not be a human. We define a framework that
allows for comparin... | computer science |
9,417 | Causal Discovery in the Presence of Measurement Error: Identifiability
Conditions | stat.ME | Measurement error in the observed values of the variables can greatly change
the output of various causal discovery methods. This problem has received much
attention in multiple fields, but it is not clear to what extent the causal
model for the measurement-error-free variables can be identified in the
presence of meas... | computer science |
9,418 | The impossibility of "fairness": a generalized impossibility result for
decisions | stat.AP | Various measures can be used to estimate bias or unfairness in a predictor.
Previous work has already established that some of these measures are
incompatible with each other. Here we show that, when groups differ in
prevalence of the predicted event, several intuitive, reasonable measures of
fairness (probability of p... | computer science |
9,419 | Bayesian Optimization for Probabilistic Programs | stat.ML | We present the first general purpose framework for marginal maximum a
posteriori estimation of probabilistic program variables. By using a series of
code transformations, the evidence of any probabilistic program, and therefore
of any graphical model, can be optimized with respect to an arbitrary subset of
its sampled ... | computer science |
9,420 | Physical problem solving: Joint planning with symbolic, geometric, and
dynamic constraints | cs.AI | In this paper, we present a new task that investigates how people interact
with and make judgments about towers of blocks. In Experiment~1, participants
in the lab solved a series of problems in which they had to re-configure three
blocks from an initial to a final configuration. We recorded whether they used
one hand ... | computer science |
9,421 | "I can assure you [$\ldots$] that it's going to be all right" -- A
definition, case for, and survey of algorithmic assurances in human-autonomy
trust relationships | cs.CY | As technology become more advanced, those who design, use and are otherwise
affected by it want to know that it will perform correctly, and understand why
it does what it does, and how to use it appropriately. In essence they want to
be able to trust the systems that are being designed. In this survey we present
assura... | computer science |
9,422 | Beyond the technical challenges for deploying Machine Learning solutions
in a software company | cs.HC | Recently software development companies started to embrace Machine Learning
(ML) techniques for introducing a series of advanced functionality in their
products such as personalisation of the user experience, improved search,
content recommendation and automation. The technical challenges for tackling
these problems ar... | computer science |
9,423 | Optimization of Ensemble Supervised Learning Algorithms for Increased
Sensitivity, Specificity, and AUC of Population-Based Colorectal Cancer
Screenings | stat.ML | Over 150,000 new people in the United States are diagnosed with colorectal
cancer each year. Nearly a third die from it (American Cancer Society). The
only approved noninvasive diagnosis tools currently involve fecal blood count
tests (FOBTs) or stool DNA tests. Fecal blood count tests take only five
minutes and are av... | computer science |
9,424 | On a Formal Model of Safe and Scalable Self-driving Cars | cs.RO | In recent years, car makers and tech companies have been racing towards self
driving cars. It seems that the main parameter in this race is who will have
the first car on the road. The goal of this paper is to add to the equation two
additional crucial parameters. The first is standardization of safety assurance
--- wh... | computer science |
9,425 | Deep Learning for Accelerated Reliability Analysis of Infrastructure
Networks | cs.CE | Natural disasters can have catastrophic impacts on the functionality of
infrastructure systems and cause severe physical and socio-economic losses.
Given budget constraints, it is crucial to optimize decisions regarding
mitigation, preparedness, response, and recovery practices for these systems.
This requires accurate... | computer science |
9,426 | Learning from lions: inferring the utility of agents from their
trajectories | cs.AI | We build a model using Gaussian processes to infer a spatio-temporal vector
field from observed agent trajectories. Significant landmarks or influence
points in agent surroundings are jointly derived through vector calculus
operations that indicate presence of sources and sinks. We evaluate these
influence points by us... | computer science |
9,427 | On labeling Android malware signatures using minhashing and further
classification with Structural Equation Models | cs.CR | Multi-scanner Antivirus systems provide insightful information on the nature
of a suspect application; however there is often a lack of consensus and
consistency between different Anti-Virus engines. In this article, we analyze
more than 250 thousand malware signatures generated by 61 different Anti-Virus
engines after... | computer science |
9,428 | Towards personalized human AI interaction - adapting the behavior of AI
agents using neural signatures of subjective interest | cs.HC | Reinforcement Learning AI commonly uses reward/penalty signals that are
objective and explicit in an environment -- e.g. game score, completion time,
etc. -- in order to learn the optimal strategy for task performance. However,
Human-AI interaction for such AI agents should include additional reinforcement
that is impl... | computer science |
9,429 | A Categorical Approach for Recognizing Emotional Effects of Music | cs.AI | Recently, digital music libraries have been developed and can be plainly
accessed. Latest research showed that current organization and retrieval of
music tracks based on album information are inefficient. Moreover, they
demonstrated that people use emotion tags for music tracks in order to search
and retrieve them. In... | computer science |
9,430 | Generalized Quantum Reinforcement Learning with Quantum Technologies | cs.AI | We propose a protocol to perform generalized quantum reinforcement learning
with quantum technologies. At variance with recent results on quantum
reinforcement learning with superconducting circuits [L. Lamata, Sci. Rep. 7,
1609 (2017)], in our current protocol coherent feedback during the learning
process is not requi... | computer science |
9,431 | Deep Haptic Model Predictive Control for Robot-Assisted Dressing | cs.RO | Robot-assisted dressing offers an opportunity to benefit the lives of many
people with disabilities, such as some older adults. However, robots currently
lack common sense about the physical implications of their actions on people.
The physical implications of dressing are complicated by non-rigid garments,
which can r... | computer science |
9,432 | Duality-free Methods for Stochastic Composition Optimization | stat.ML | We consider the composition optimization with two expected-value functions in
the form of $\frac{1}{n}\sum\nolimits_{i = 1}^n F_i(\frac{1}{m}\sum\nolimits_{j
= 1}^m G_j(x))+R(x)$, { which formulates many important problems in statistical
learning and machine learning such as solving Bellman equations in
reinforcement l... | computer science |
9,433 | Intelligent Fault Analysis in Electrical Power Grids | cs.SY | Power grids are one of the most important components of infrastructure in
today's world. Every nation is dependent on the security and stability of its
own power grid to provide electricity to the households and industries. A
malfunction of even a small part of a power grid can cause loss of
productivity, revenue and i... | computer science |
9,434 | Parkinson's Disease Digital Biomarker Discovery with Optimized
Transitions and Inferred Markov Emissions | cs.AI | We search for digital biomarkers from Parkinson's Disease by observing
approximate repetitive patterns matching hypothesized step and stride periodic
cycles. These observations were modeled as a cycle of hidden states with
randomness allowing deviation from a canonical pattern of transitions and
emissions, under the hy... | computer science |
9,435 | Efficiency Analysis of ASP Encodings for Sequential Pattern Mining Tasks | cs.AI | This article presents the use of Answer Set Programming (ASP) to mine
sequential patterns. ASP is a high-level declarative logic programming paradigm
for high level encoding combinatorial and optimization problem solving as well
as knowledge representation and reasoning. Thus, ASP is a good candidate for
implementing p... | computer science |
9,436 | A generalised framework for detailed classification of swimming paths
inside the Morris Water Maze | cs.AI | The Morris Water Maze is commonly used in behavioural neuroscience for the
study of spatial learning with rodents. Over the years, various methods of
analysing rodent data collected in this task have been proposed. These methods
span from classical performance measurements (e.g. escape latency, rodent
speed, quadrant p... | computer science |
9,437 | Quantifying Performance of Bipedal Standing with Multi-channel EMG | stat.ML | Spinal cord stimulation has enabled humans with motor complete spinal cord
injury (SCI) to independently stand and recover some lost autonomic function.
Quantifying the quality of bipedal standing under spinal stimulation is
important for spinal rehabilitation therapies and for new strategies that seek
to combine spina... | computer science |
9,438 | Automated Algorithm Selection on Continuous Black-Box Problems By
Combining Exploratory Landscape Analysis and Machine Learning | stat.ML | In this paper, we build upon previous work on designing informative and
efficient Exploratory Landscape Analysis features for characterizing problems'
landscapes and show their effectiveness in automatically constructing algorithm
selection models in continuous black-box optimization problems. Focussing on
algorithm pe... | computer science |
9,439 | Representation Learning for Scale-free Networks | cs.SI | Network embedding aims to learn the low-dimensional representations of
vertexes in a network, while structure and inherent properties of the network
is preserved. Existing network embedding works primarily focus on preserving
the microscopic structure, such as the first- and second-order proximity of
vertexes, while th... | computer science |
9,440 | Gated Recurrent Networks for Seizure Detection | eess.SP | Recurrent Neural Networks (RNNs) with sophisticated units that implement a
gating mechanism have emerged as powerful technique for modeling sequential
signals such as speech or electroencephalography (EEG). The latter is the focus
on this paper. A significant big data resource, known as the TUH EEG Corpus
(TUEEG), has ... | computer science |
9,441 | Robust Propensity Score Computation Method based on Machine Learning
with Label-corrupted Data | stat.ME | In biostatistics, propensity score is a common approach to analyze the
imbalance of covariate and process confounding covariates to eliminate
differences between groups. While there are an abundant amount of methods to
compute propensity score, a common issue of them is the corrupted labels in the
dataset. For example,... | computer science |
9,442 | Estimating Heterogeneous Consumer Preferences for Restaurants and Travel
Time Using Mobile Location Data | econ.EM | This paper analyzes consumer choices over lunchtime restaurants using data
from a sample of several thousand anonymous mobile phone users in the San
Francisco Bay Area. The data is used to identify users' approximate typical
morning location, as well as their choices of lunchtime restaurants. We build a
model where res... | computer science |
9,443 | HONE: Higher-Order Network Embeddings | stat.ML | This paper describes a general framework for learning Higher-Order Network
Embeddings (HONE) from graph data based on network motifs. The HONE framework
is highly expressive and flexible with many interchangeable components. The
experimental results demonstrate the effectiveness of learning higher-order
network represe... | computer science |
9,444 | Human-Machine Inference Networks For Smart Decision Making:
Opportunities and Challenges | cs.HC | The emerging paradigm of Human-Machine Inference Networks (HuMaINs) combines
complementary cognitive strengths of humans and machines in an intelligent
manner to tackle various inference tasks and achieves higher performance than
either humans or machines by themselves. While inference performance
optimization techniqu... | computer science |
9,445 | Over-representation of Extreme Events in Decision-Making: A Rational
Metacognitive Account | cs.AI | The Availability bias, manifested in the over-representation of extreme
eventualities in decision-making, is a well-known cognitive bias, and is
generally taken as evidence of human irrationality. In this work, we present
the first rational, metacognitive account of the Availability bias, formally
articulated at Marr's... | computer science |
9,446 | A Rational Distributed Process-level Account of Independence Judgment | cs.AI | It is inconceivable how chaotic the world would look to humans, faced with
innumerable decisions a day to be made under uncertainty, had they been lacking
the capacity to distinguish the relevant from the irrelevant---a capacity which
computationally amounts to handling probabilistic independence relations. The
highly ... | computer science |
9,447 | Learning Role-based Graph Embeddings | stat.ML | Random walks are at the heart of many existing network embedding methods.
However, such algorithms have many limitations that arise from the use of
random walks, e.g., the features resulting from these methods are unable to
transfer to new nodes and graphs as they are tied to vertex identity. In this
work, we introduce... | computer science |
9,448 | ATPboost: Learning Premise Selection in Binary Setting with ATP Feedback | cs.AI | ATPboost is a system for solving sets of large-theory problems by
interleaving ATP runs with state-of-the-art machine learning of premise
selection from the proofs. Unlike many previous approaches that use multi-label
setting, the learning is implemented as binary classification that estimates
the pairwise-relevance of... | computer science |
9,449 | The Need for Speed of AI Applications: Performance Comparison of Native
vs. Browser-based Algorithm Implementations | cs.AI | AI applications pose increasing demands on performance, so it is not
surprising that the era of client-side distributed software is becoming
important. On top of many AI applications already using mobile hardware, and
even browsers for computationally demanding AI applications, we are already
witnessing the emergence o... | computer science |
9,450 | Crowd ideation of supervised learning problems | cs.HC | Crowdsourcing is an important avenue for collecting machine learning data,
but crowdsourcing can go beyond simple data collection by employing the
creativity and wisdom of crowd workers. Yet crowd participants are unlikely to
be experts in statistics or predictive modeling, and it is not clear how well
non-experts can ... | computer science |
9,451 | SentRNA: Improving computational RNA design by incorporating a prior of
human design strategies | cs.AI | Designing RNA sequences that fold into specific structures and perform
desired biological functions is an emerging field in bioengineering with broad
applications from intracellular chemical catalysis to cancer therapy via
selective gene silencing. Effective RNA design requires first solving the
inverse folding problem... | computer science |
9,452 | Valuing knowledge, information and agency in Multi-agent Reinforcement
Learning: a case study in smart buildings | cs.MA | Increasing energy efficiency in buildings can reduce costs and emissions
substantially. Historically, this has been treated as a local, or single-agent,
optimization problem. However, many buildings utilize the same types of thermal
equipment e.g. electric heaters and hot water vessels. During operation,
occupants in t... | computer science |
9,453 | Categorizing Variants of Goodhart's Law | cs.AI | There are several distinct failure modes for overoptimization of systems on
the basis of metrics. This occurs when a metric which can be used to improve a
system is used to an extent that further optimization is ineffective or
harmful, and is sometimes termed Goodhart's Law. This class of failure is often
poorly unders... | computer science |
9,454 | Oracle Complexity and Nontransitivity in Pattern Recognition | cs.CC | Different mathematical models of recognition processes are known. In the
present paper we consider a pattern recognition algorithm as an oracle
computation on a Turing machine. Such point of view seems to be useful in
pattern recognition as well as in recursion theory. Use of recursion theory in
pattern recognition sho... | computer science |
9,455 | The Generalized Universal Law of Generalization | cs.CV | It has been argued by Shepard that there is a robust psychological law that
relates the distance between a pair of items in psychological space and the
probability that they will be confused with each other. Specifically, the
probability of confusion is a negative exponential function of the distance
between the pair o... | computer science |
9,456 | Cyborg Systems as Platforms for Computer-Vision Algorithm-Development
for Astrobiology | cs.CV | Employing the allegorical imagery from the film "The Matrix", we motivate and
discuss our `Cyborg Astrobiologist' research program. In this research program,
we are using a wearable computer and video camcorder in order to test and train
a computer-vision system to be a field-geologist and field-astrobiologist. | computer science |
9,457 | ScheduleNanny: Using GPS to Learn the User's Significant Locations,
Travel Times and Schedule | cs.AI | As computing technology becomes more pervasive, personal devices such as the
PDA, cell-phone, and notebook should use context to determine how to act.
Location is one form of context that can be used in many ways. We present a
multiple-device system that collects and clusters GPS data into significant
locations. These ... | computer science |
9,458 | Fast Lexically Constrained Viterbi Algorithm (FLCVA): Simultaneous
Optimization of Speed and Memory | cs.CV | Lexical constraints on the input of speech and on-line handwriting systems
improve the performance of such systems. A significant gain in speed can be
achieved by integrating in a digraph structure the different Hidden Markov
Models (HMM) corresponding to the words of the relevant lexicon. This
integration avoids redun... | computer science |
9,459 | Applying MDL to Learning Best Model Granularity | cs.AI | The Minimum Description Length (MDL) principle is solidly based on a provably
ideal method of inference using Kolmogorov complexity. We test how the theory
behaves in practice on a general problem in model selection: that of learning
the best model granularity. The performance of a model depends critically on
the granu... | computer science |
9,460 | The Expressive Power of Binary Submodular Functions | cs.DM | It has previously been an open problem whether all Boolean submodular
functions can be decomposed into a sum of binary submodular functions over a
possibly larger set of variables. This problem has been considered within
several different contexts in computer science, including computer vision,
artificial intelligence,... | computer science |
9,461 | FaceBots: Steps Towards Enhanced Long-Term Human-Robot Interaction by
Utilizing and Publishing Online Social Information | cs.RO | Our project aims at supporting the creation of sustainable and meaningful
longer-term human-robot relationships through the creation of embodied robots
with face recognition and natural language dialogue capabilities, which exploit
and publish social information available on the web (Facebook). Our main
underlying expe... | computer science |
9,462 | A Model-Based Approach to Predicting Predator-Prey & Friend-Foe
Relationships in Ant Colonies | cs.AI | Understanding predator-prey relationships among insects is a challenging task
in the domain of insect-colony research. This is due to several factors
involved, such as determining whether a particular behavior is the result of a
predator-prey interaction, a friend-foe interaction or another kind of
interaction. In this... | computer science |
9,463 | Survey on Various Gesture Recognition Techniques for Interfacing
Machines Based on Ambient Intelligence | cs.AI | Gesture recognition is mainly apprehensive on analyzing the functionality of
human wits. The main goal of gesture recognition is to create a system which
can recognize specific human gestures and use them to convey information or for
device control. Hand gestures provide a separate complementary modality to
speech for ... | computer science |
9,464 | A linear framework for region-based image segmentation and inpainting
involving curvature penalization | cs.CV | We present the first method to handle curvature regularity in region-based
image segmentation and inpainting that is independent of initialization.
To this end we start from a new formulation of length-based optimization
schemes, based on surface continuation constraints, and discuss the connections
to existing schem... | computer science |
9,465 | Inferring 3D Articulated Models for Box Packaging Robot | cs.RO | Given a point cloud, we consider inferring kinematic models of 3D articulated
objects such as boxes for the purpose of manipulating them. While previous work
has shown how to extract a planar kinematic model (often represented as a
linear chain), such planar models do not apply to 3D objects that are composed
of segmen... | computer science |
9,466 | Active Classification: Theory and Application to Underwater Inspection | cs.RO | We discuss the problem in which an autonomous vehicle must classify an object
based on multiple views. We focus on the active classification setting, where
the vehicle controls which views to select to best perform the classification.
The problem is formulated as an extension to Bayesian active learning, and we
show co... | computer science |
9,467 | An Efficient Real Time Method of Fingertip Detection | cs.CV | Fingertips detection has been used in many applications, and it is very
popular and commonly used in the area of Human Computer Interaction these days.
This paper presents a novel time efficient method that will lead to fingertip
detection after cropping the irrelevant parts of input image. Binary silhouette
of the inp... | computer science |
9,468 | Towards Holistic Scene Understanding: Feedback Enabled Cascaded
Classification Models | cs.CV | Scene understanding includes many related sub-tasks, such as scene
categorization, depth estimation, object detection, etc. Each of these
sub-tasks is often notoriously hard, and state-of-the-art classifiers already
exist for many of them. These classifiers operate on the same raw image and
provide correlated outputs. ... | computer science |
9,469 | Contextually Guided Semantic Labeling and Search for 3D Point Clouds | cs.RO | RGB-D cameras, which give an RGB image to- gether with depths, are becoming
increasingly popular for robotic perception. In this paper, we address the task
of detecting commonly found objects in the 3D point cloud of indoor scenes
obtained from such cameras. Our method uses a graphical model that captures
various featu... | computer science |
9,470 | 3D Model Retrieval Based on Semantic and Shape Indexes | cs.IR | The size of 3D models used on the web or stored in databases is becoming
increasingly high. Then, an efficient method that allows users to find similar
3D objects for a given 3D model query has become necessary. Keywords and the
geometry of a 3D model cannot meet the needs of users' retrieval because they
do not includ... | computer science |
9,471 | Cognitive Memory Network | cs.AI | A resistive memory network that has no crossover wiring is proposed to
overcome the hardware limitations to size and functional complexity that is
associated with conventional analogue neural networks. The proposed memory
network is based on simple network cells that are arranged in a hierarchical
modular architecture.... | computer science |
9,472 | Seeing Unseeability to See the Unseeable | cs.CV | We present a framework that allows an observer to determine occluded portions
of a structure by finding the maximum-likelihood estimate of those occluded
portions consistent with visible image evidence and a consistency model. Doing
this requires determining which portions of the structure are occluded in the
first pla... | computer science |
9,473 | Spike Timing Dependent Competitive Learning in Recurrent Self Organizing
Pulsed Neural Networks Case Study: Phoneme and Word Recognition | cs.CV | Synaptic plasticity seems to be a capital aspect of the dynamics of neural
networks. It is about the physiological modifications of the synapse, which
have like consequence a variation of the value of the synaptic weight. The
information encoding is based on the precise timing of single spike events that
is based on th... | computer science |
9,474 | Utility-Based Control for Computer Vision | cs.CV | Several key issues arise in implementing computer vision recognition of world
objects in terms of Bayesian networks. Computational efficiency is a driving
force. Perceptual networks are very deep, typically fifteen levels of
structure. Images are wide, e.g., an unspecified-number of edges may appear
anywhere in an imag... | computer science |
9,475 | Separating the Real from the Synthetic: Minutiae Histograms as
Fingerprints of Fingerprints | cs.CV | In this study we show that by the current state-of-the-art synthetically
generated fingerprints can easily be discriminated from real fingerprints. We
propose a method based on second order extended minutiae histograms (MHs) which
can distinguish between real and synthetic prints with very high accuracy. MHs
provide a ... | computer science |
9,476 | ROTUNDE - A Smart Meeting Cinematography Initiative: Tools, Datasets,
and Benchmarks for Cognitive Interpretation and Control | cs.AI | We construe smart meeting cinematography with a focus on professional
situations such as meetings and seminars, possibly conducted in a distributed
manner across socio-spatially separated groups. The basic objective in smart
meeting cinematography is to interpret professional interactions involving
people, and automati... | computer science |
9,477 | Cognitive Interpretation of Everyday Activities: Toward Perceptual
Narrative Based Visuo-Spatial Scene Interpretation | cs.AI | We position a narrative-centred computational model for high-level knowledge
representation and reasoning in the context of a range of assistive
technologies concerned with "visuo-spatial perception and cognition" tasks. Our
proposed narrative model encompasses aspects such as \emph{space, events,
actions, change, and ... | computer science |
9,478 | Two-Dimensional ARMA Modeling for Breast Cancer Detection and
Classification | cs.AI | We propose a new model-based computer-aided diagnosis (CAD) system for tumor
detection and classification (cancerous v.s. benign) in breast images.
Specifically, we show that (x-ray, ultrasound and MRI) images can be accurately
modeled by two-dimensional autoregressive-moving average (ARMA) random fields.
We derive a t... | computer science |
9,479 | Learning Human Activities and Object Affordances from RGB-D Videos | cs.RO | Understanding human activities and object affordances are two very important
skills, especially for personal robots which operate in human environments. In
this work, we consider the problem of extracting a descriptive labeling of the
sequence of sub-activities being performed by a human, and more importantly, of
their... | computer science |
9,480 | Optimization in Differentiable Manifolds in Order to Determine the
Method of Construction of Prehistoric Wall-Paintings | cs.CV | In this paper a general methodology is introduced for the determination of
potential prototype curves used for the drawing of prehistoric wall-paintings.
The approach includes a) preprocessing of the wall-paintings contours to
properly partition them, according to their curvature, b) choice of prototype
curves families... | computer science |
9,481 | To Fall Or Not To Fall: A Visual Approach to Physical Stability
Prediction | cs.CV | Understanding physical phenomena is a key competence that enables humans and
animals to act and interact under uncertain perception in previously unseen
environments containing novel object and their configurations. Developmental
psychology has shown that such skills are acquired by infants from observations
at a very ... | computer science |
9,482 | Deep Cross Residual Learning for Multitask Visual Recognition | cs.CV | Residual learning has recently surfaced as an effective means of constructing
very deep neural networks for object recognition. However, current incarnations
of residual networks do not allow for the modeling and integration of complex
relations between closely coupled recognition tasks or across domains. Such
problems... | computer science |
9,483 | The Curious Robot: Learning Visual Representations via Physical
Interactions | cs.CV | What is the right supervisory signal to train visual representations? Current
approaches in computer vision use category labels from datasets such as
ImageNet to train ConvNets. However, in case of biological agents, visual
representation learning does not require millions of semantic labels. We argue
that biological a... | computer science |
9,484 | Autonomously Learning to Visually Detect Where Manipulation Will Succeed | cs.RO | Visual features can help predict if a manipulation behavior will succeed at a
given location. For example, the success of a behavior that flips light
switches depends on the location of the switch. Within this paper, we present
methods that enable a mobile manipulator to autonomously learn a function that
takes an RGB ... | computer science |
9,485 | Medical Image Fusion: A survey of the state of the art | cs.CV | Medical image fusion is the process of registering and combining multiple
images from single or multiple imaging modalities to improve the imaging
quality and reduce randomness and redundancy in order to increase the clinical
applicability of medical images for diagnosis and assessment of medical
problems. Multi-modal ... | computer science |
9,486 | Video Face Editing Using Temporal-Spatial-Smooth Warping | cs.CV | Editing faces in videos is a popular yet challenging aspect of computer
vision and graphics, which encompasses several applications including facial
attractiveness enhancement, makeup transfer, face replacement, and expression
manipulation. Simply applying image-based warping algorithms to video-based
face editing prod... | computer science |
9,487 | Classifying sequences by the optimized dissimilarity space embedding
approach: a case study on the solubility analysis of the E. coli proteome | cs.CV | We evaluate a version of the recently-proposed classification system named
Optimized Dissimilarity Space Embedding (ODSE) that operates in the input space
of sequences of generic objects. The ODSE system has been originally presented
as a classification system for patterns represented as labeled graphs. However,
since ... | computer science |
9,488 | Building with Drones: Accurate 3D Facade Reconstruction using MAVs | cs.RO | Automatic reconstruction of 3D models from images using multi-view
Structure-from-Motion methods has been one of the most fruitful outcomes of
computer vision. These advances combined with the growing popularity of Micro
Aerial Vehicles as an autonomous imaging platform, have made 3D vision tools
ubiquitous for large n... | computer science |
9,489 | Group Event Detection with a Varying Number of Group Members for Video
Surveillance | cs.CV | This paper presents a novel approach for automatic recognition of group
activities for video surveillance applications. We propose to use a group
representative to handle the recognition with a varying number of group
members, and use an Asynchronous Hidden Markov Model (AHMM) to model the
relationship between people. ... | computer science |
9,490 | Reduced Basis Decomposition: a Certified and Fast Lossy Data Compression
Algorithm | math.NA | Dimension reduction is often needed in the area of data mining. The goal of
these methods is to map the given high-dimensional data into a low-dimensional
space preserving certain properties of the initial data. There are two kinds of
techniques for this purpose. The first, projective methods, builds an explicit
linear... | computer science |
9,491 | CDVAE: Co-embedding Deep Variational Auto Encoder for Conditional
Variational Generation | cs.CV | Problems such as predicting a new shading field (Y) for an image (X) are
ambiguous: many very distinct solutions are good. Representing this ambiguity
requires building a conditional model P(Y|X) of the prediction, conditioned on
the image. Such a model is difficult to train, because we do not usually have
training dat... | computer science |
9,492 | Multiple Instance Learning: A Survey of Problem Characteristics and
Applications | cs.CV | Multiple instance learning (MIL) is a form of weakly supervised learning
where training instances are arranged in sets, called bags, and a label is
provided for the entire bag. This formulation is gaining interest because it
naturally fits various problems and allows to leverage weakly labeled data.
Consequently, it ha... | computer science |
9,493 | Accelerated Convolutions for Efficient Multi-Scale Time to Contact
Computation in Julia | cs.CV | Convolutions have long been regarded as fundamental to applied mathematics,
physics and engineering. Their mathematical elegance allows for common tasks
such as numerical differentiation to be computed efficiently on large data
sets. Efficient computation of convolutions is critical to artificial
intelligence in real-t... | computer science |
9,494 | Multi-q Analysis of Image Patterns | cs.AI | This paper studies the use of the Tsallis Entropy versus the classic
Boltzmann-Gibbs-Shannon entropy for classifying image patterns. Given a
database of 40 pattern classes, the goal is to determine the class of a given
image sample. Our experiments show that the Tsallis entropy encoded in a
feature vector for different... | computer science |
9,495 | Fast Exact Search in Hamming Space with Multi-Index Hashing | cs.CV | There is growing interest in representing image data and feature descriptors
using compact binary codes for fast near neighbor search. Although binary codes
are motivated by their use as direct indices (addresses) into a hash table,
codes longer than 32 bits are not being used as such, as it was thought to be
ineffecti... | computer science |
9,496 | Understanding Humans' Strategies in Maze Solving | cs.CV | Navigating through a visual maze relies on the strategic use of eye movements
to select and identify the route. When navigating the maze, there are
trade-offs between exploring to the environment and relying on memory. This
study examined strategies used to navigating through novel and familiar mazes
that were viewed f... | computer science |
9,497 | Integration of 3D Object Recognition and Planning for Robotic
Manipulation: A Preliminary Report | cs.AI | We investigate different approaches to integrating object recognition and
planning in a tabletop manipulation domain with the set of objects used in the
2012 RoboCup@Work competition. Results of our preliminary experiments show
that, with some approaches, close integration of perception and planning
improves the qualit... | computer science |
9,498 | RANSAC: Identification of Higher-Order Geometric Features and
Applications in Humanoid Robot Soccer | cs.RO | The ability for an autonomous agent to self-localise is directly proportional
to the accuracy and precision with which it can perceive salient features
within its local environment. The identification of such features by
recognising geometric profile allows robustness against lighting variations,
which is necessary in ... | computer science |
9,499 | Tree-based iterated local search for Markov random fields with
applications in image analysis | cs.AI | The \emph{maximum a posteriori} (MAP) assignment for general structure Markov
random fields (MRFs) is computationally intractable. In this paper, we exploit
tree-based methods to efficiently address this problem. Our novel method, named
Tree-based Iterated Local Search (T-ILS) takes advantage of the tractability of
tre... | computer science |
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