justin

Today I read a paper titled “Computer Model of a “Sense of Humour”. II. Realization in Neural Networks”

The abstract is:
The computer realization of a “sense of humour” requires the creation of an algorithm for solving the “linguistic problem”, i.e.

the problem of recognizing a continuous sequence of polysemantic images.

Such algorithm may be realized in the Hopfield model of a neural network after its proper modification.

Today I read a paper titled “3D Face Recognition with Sparse Spherical Representations”

The abstract is:
This paper addresses the problem of 3D face recognition using simultaneous sparse approximations on the sphere.

The 3D face point clouds are first aligned with a novel and fully automated registration process.

They are then represented as signals on the 2D sphere in order to preserve depth and geometry information.

Next, we implement a dimensionality reduction process with simultaneous sparse approximations and subspace projection.

It permits to represent each 3D face by only a few spherical functions that are able to capture the salient facial characteristics, and hence to preserve the discriminant facial information.

We eventually perform recognition by effective matching in the reduced space, where Linear Discriminant Analysis can be further activated for improved recognition performance.

The 3D face recognition algorithm is evaluated on the FRGC v.1.0 data set, where it is shown to outperform classical state-of-the-art solutions that work with depth images.

Today I read a paper titled “Learning Unification-Based Natural Language Grammars”

The abstract is:
When parsing unrestricted language, wide-covering grammars often undergenerate.

Undergeneration can be tackled either by sentence correction, or by grammar correction.

This thesis concentrates upon automatic grammar correction (or machine learning of grammar) as a solution to the problem of undergeneration.

Broadly speaking, grammar correction approaches can be classified as being either {\it data-driven}, or {\it model-based}.

Data-driven learners use data-intensive methods to acquire grammar.

They typically use grammar formalisms unsuited to the needs of practical text processing and cannot guarantee that the resulting grammar is adequate for subsequent semantic interpretation.

That is, data-driven learners acquire grammars that generate strings that humans would judge to be grammatically ill-formed (they {\it overgenerate}) and fail to assign linguistically plausible parses.

Model-based learners are knowledge-intensive and are reliant for success upon the completeness of a {\it model of grammaticality}.

But in practice, the model will be incomplete.

Given that in this thesis we deal with undergeneration by learning, we hypothesise that the combined use of data-driven and model-based learning would allow data-driven learning to compensate for model-based learning’s incompleteness, whilst model-based learning would compensate for data-driven learning’s unsoundness.

We describe a system that we have used to test the hypothesis empirically.

The system combines data-driven and model-based learning to acquire unification-based grammars that are more suitable for practical text parsing.

Using the Spoken English Corpus as data, and by quantitatively measuring undergeneration, overgeneration and parse plausibility, we show that this hypothesis is correct..

Today I read a paper titled “It’s Not What You Have, But How You Use It: Compromises in Mobile Device Use”

The abstract is:
As users begin to use many more devices for personal information management (PIM) than just the traditional desktop computer, it is essential for HCI researchers to understand how these devices are being used in the wild and their roles in users’ information environments.

We conducted a study of 220 knowledge workers about their devices, the activities they performed on each, and the groups of devices used together.

Our findings indicate that several devices are often used in groups; integrated multi-function portable devices have begun to replace single-function devices for communication (e.g.

email and IM).

Users use certain features opportunistically because they happen to be carrying a multi-function device with them.

The use of multiple devices and multi-function devices is fraught with compromises as users must choose and make trade-offs among various factors.

Today I read a paper titled “Gesture Recognition with a Focus on Important Actions by Using a Path Searching Method in Weighted Graph”

The abstract is:
This paper proposes a method of gesture recognition with a focus on important actions for distinguishing similar gestures.

The method generates a partial action sequence by using optical flow images, expresses the sequence in the eigenspace, and checks the feature vector sequence by applying an optimum path-searching method of weighted graph to focus the important actions.

Also presented are the results of an experiment on the recognition of similar sign language words.

Today I read a paper titled “A Framework for Designing 3D Virtual Environments”

The abstract is:
The process of design and development of virtual environments can be supported by tools and frameworks, to save time in technical aspects and focusing on the content.

In this paper we present an academic framework which provides several levels of abstraction to ease this work.

It includes state-of-the-art components we devised or integrated adopting open-source solutions in order to face specific problems.

Its architecture is modular and customizable, the code is open-source.

Today I read a paper titled “Singularity Analysis of Limited-dof Parallel Manipulators using Grassmann-Cayley Algebra”

The abstract is:
This paper characterizes geometrically the singularities of limited DOF parallel manipulators.

The geometric conditions associated with the dependency of six Pl\”ucker vector of lines (finite and infinite) constituting the rows of the inverse Jacobian matrix are formulated using Grassmann-Cayley algebra.

Manipulators under consideration do not need to have a passive spherical joint somewhere in each leg.

This study is illustrated with three example robots .

Today I read a paper titled “Robot Swarms in an Uncertain World: Controllable Adaptability”

The abstract is:
There is a belief that complexity and chaos are essential for adaptability.

But life deals with complexity every moment, without the chaos that engineers fear so, by invoking goal-directed behaviour.

Goals can be programmed.

That is why living organisms give us hope to achieve adaptability in robots.

In this paper a method for the description of a goal-directed, or programmed, behaviour, interacting with uncertainty of environment, is described.

We suggest reducing the structural (goals, intentions) and stochastic components (probability to realise the goal) of individual behaviour to random variables with nominal values to apply probabilistic approach.

This allowed us to use a Normalized Entropy Index to detect the system state by estimating the contribution of each agent to the group behaviour.

The number of possible group states is 27.

We argue that adaptation has a limited number of possible paths between these 27 states.

Paths and states can be programmed so that after adjustment to any particular case of task and conditions, adaptability will never involve chaos.

We suggest the application of the model to operation of robots or other devices in remote and/or dangerous places.

Today I read a paper titled “An Estimation of the Shortest and Largest Average Path Length in Graphs of Given Density”

The abstract is:
Many real world networks (graphs) are observed to be ‘small worlds’, i.e., the average path length among nodes is small.

On the other hand, it is somewhat unclear what other average path length values networks can produce.

In particular, it is not known what the maximum and the minimum average path length values are.

In this paper we provide a lower estimation for the shortest average path length (l) values in connected networks, and the largest possible average path length values in networks with given size and density.

To the latter end, we construct a special family of graphs and calculate their average path lengths.

We also demonstrate the correctness of our estimation by simulations.

Today I read a paper titled “Unstructured Human Activity Detection from RGBD Images”

The abstract is:
Being able to detect and recognize human activities is essential for several applications, including personal assistive robotics.

In this paper, we perform detection and recognition of unstructured human activity in unstructured environments.

We use a RGBD sensor (Microsoft Kinect) as the input sensor, and compute a set of features based on human pose and motion, as well as based on image and pointcloud information.

Our algorithm is based on a hierarchical maximum entropy Markov model (MEMM), which considers a person’s activity as composed of a set of sub-activities.

We infer the two-layered graph structure using a dynamic programming approach.

We test our algorithm on detecting and recognizing twelve different activities performed by four people in different environments, such as a kitchen, a living room, an office, etc., and achieve good performance even when the person was not seen before in the training set.

Today I read a paper titled “A Vortex Method for Bi-phasic Fluids Interacting with Rigid Bodies”

The abstract is:
We present an accurate Lagrangian method based on vortex particles, level-sets, and immersed boundary methods, for animating the interplay between two fluids and rigid solids.

We show that a vortex method is a good choice for simulating bi-phase flow, such as liquid and gas, with a good level of realism.

Vortex particles are localized at the interfaces between the two fluids and within the regions of high turbulence.

We gain local precision and efficiency from the stable advection permitted by the vorticity formulation.

Moreover, our numerical method straightforwardly solves the two-way coupling problem between the fluids and animated rigid solids.

This new approach is validated through numerical comparisons with reference experiments from the computational fluid community.

We also show that the visually appealing results obtained in the CG community can be reproduced with increased efficiency and an easier implementation.

Today I read a paper titled “Probabilistically Safe Vehicle Control in a Hostile Environment”

The abstract is:
In this paper we present an approach to control a vehicle in a hostile environment with static obstacles and moving adversaries.

The vehicle is required to satisfy a mission objective expressed as a temporal logic specification over a set of properties satisfied at regions of a partitioned environment.

We model the movements of adversaries in between regions of the environment as Poisson processes.

Furthermore, we assume that the time it takes for the vehicle to traverse in between two facets of each region is exponentially distributed, and we obtain the rate of this exponential distribution from a simulator of the environment.

We capture the motion of the vehicle and the vehicle updates of adversaries distributions as a Markov Decision Process.

Using tools in Probabilistic Computational Tree Logic, we find a control strategy for the vehicle that maximizes the probability of accomplishing the mission objective.

We demonstrate our approach with illustrative case studies.

Today I read a paper titled “A path following algorithm for the graph matching problem”

The abstract is:
We propose a convex-concave programming approach for the labeled weighted graph matching problem.

The convex-concave programming formulation is obtained by rewriting the weighted graph matching problem as a least-square problem on the set of permutation matrices and relaxing it to two different optimization problems: a quadratic convex and a quadratic concave optimization problem on the set of doubly stochastic matrices.

The concave relaxation has the same global minimum as the initial graph matching problem, but the search for its global minimum is also a hard combinatorial problem.

We therefore construct an approximation of the concave problem solution by following a solution path of a convex-concave problem obtained by linear interpolation of the convex and concave formulations, starting from the convex relaxation.

This method allows to easily integrate the information on graph label similarities into the optimization problem, and therefore to perform labeled weighted graph matching.

The algorithm is compared with some of the best performing graph matching methods on four datasets: simulated graphs, QAPLib, retina vessel images and handwritten chinese characters.

In all cases, the results are competitive with the state-of-the-art.

Today I read a paper titled “Established Clustering Procedures for Network Analysis”

The abstract is:
In light of the burgeoning interest in network analysis in the new millenium, we bring to the attention of contemporary network theorists, a two-stage double-standarization and hierarchical clustering (single-linkage-like) procedure devised in 1974.

In its many applications over the next decade–primarily to the migration flows between geographic subdivisions within nations–the presence was often revealed of “hubs”.

These are, typically, “cosmopolitan/non-provincial” areas–such as the French capital, Paris–which send and receive people relatively broadly across their respective nations.

Additionally, this two-stage procedure–which “might very well be the most successful application of cluster analysis” (R.

C.

Dubes)–has detected many (physically or socially) isolated groups (regions) of areas, such as those forming the southern islands, Shikoku and Kyushu, of Japan, the Italian islands of Sardinia and Sicily, and the New England region of the United States.

Further, we discuss a (complementary) approach developed in 1976, involving the application of the max-flow/min-cut theorem to raw/non-standardized flows.

Today I read a paper titled “Colorization of Natural Images via L1 Optimization”

The abstract is:
Natural images in the colour space YUV have been observed to have a non-Gaussian, heavy tailed distribution (called ‘sparse’) when the filter G(U)(r) = U(r) – sum_{s \in N(r)} w{(Y)_{rs}} U(s), is applied to the chromacity channel U (and equivalently to V), where w is a weighting function constructed from the intensity component Y [1].

In this paper we develop Bayesian analysis of the colorization problem using the filter response as a regularization term to arrive at a non-convex optimization problem.

This problem is convexified using L1 optimization which often gives the same results for sparse signals [2].

It is observed that L1 optimization, in many cases, over-performs the famous colorization algorithm by Levin et al [3].

Today I read a paper titled “Feature Dynamic Bayesian Networks”

The abstract is:
Feature Markov Decision Processes (PhiMDPs) are well-suited for learning agents in general environments.

Nevertheless, unstructured (Phi)MDPs are limited to relatively simple environments.

Structured MDPs like Dynamic Bayesian Networks (DBNs) are used for large-scale real-world problems.

In this article I extend PhiMDP to PhiDBN.

The primary contribution is to derive a cost criterion that allows to automatically extract the most relevant features from the environment, leading to the “best” DBN representation.

I discuss all building blocks required for a complete general learning algorithm.

Today I read a paper titled “Discrete Complex Structure on Surfel Surfaces”

The abstract is:
This paper defines a theory of conformal parametrization of digital surfaces made of surfels equipped with a normal vector.

The main idea is to locally project each surfel to the tangent plane, therefore deforming its aspect-ratio.

It is a generalization of the theory known for polyhedral surfaces.

The main difference is that the conformal ratios that appear are no longer real in general.

It yields a generalization of the standard Laplacian on weighted graphs.

Today I read a paper titled “Fairness in Combinatorial Auctioning Systems”

The abstract is:
One of the Multi-Agent Systems that is widely used by various government agencies, buyers and sellers in a market economy, in such a manner so as to attain optimized resource allocation, is the Combinatorial Auctioning System (CAS).

We study another important aspect of resource allocations in CAS, namely fairness.

We present two important notions of fairness in CAS, extended fairness and basic fairness.

We give an algorithm that works by incorporating a metric to ensure fairness in a CAS that uses the Vickrey-Clark-Groves (VCG) mechanism, and uses an algorithm of Sandholm to achieve optimality.

Mathematical formulations are given to represent measures of extended fairness and basic fairness.

Today I read a paper titled “Increasing Linear Dynamic Range of Commercial Digital Photocamera Used in Imaging Systems with Optical Coding”

The abstract is:
Methods of increasing linear optical dynamic range of commercial photocamera for optical-digital imaging systems are described.

Use of such methods allows to use commercial photocameras for optical measurements.

Experimental results are reported.

Today I read a paper titled “Controlling wheelchairs by body motions: A learning framework for the adaptive remapping of space”

The abstract is:
Learning to operate a vehicle is generally accomplished by forming a new cognitive map between the body motions and extrapersonal space.

Here, we consider the challenge of remapping movement-to-space representations in survivors of spinal cord injury, for the control of powered wheelchairs.

Our goal is to facilitate this remapping by developing interfaces between residual body motions and navigational commands that exploit the degrees of freedom that disabled individuals are most capable to coordinate.

We present a new framework for allowing spinal cord injured persons to control powered wheelchairs through signals derived from their residual mobility.

The main novelty of this approach lies in substituting the more common joystick controllers of powered wheelchairs with a sensor shirt.

This allows the whole upper body of the user to operate as an adaptive joystick.

Considerations about learning and risks have lead us to develop a safe testing environment in 3D Virtual Reality.

A Personal Augmented Reality Immersive System (PARIS) allows us to analyse learning skills and provide users with an adequate training to control a simulated wheelchair through the signals generated by body motions in a safe environment.

We provide a description of the basic theory, of the development phases and of the operation of the complete system.

We also present preliminary results illustrating the processing of the data and supporting of the feasibility of this approach.

Today I read a paper titled “Spatial Networks”

The abstract is:
Complex systems are very often organized under the form of networks where nodes and edges are embedded in space.

Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, neural networks, are all examples where space is relevant and where topology alone does not contain all the information.

Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields ranging from urbanism to epidemiology.

An important consequence of space on networks is that there is a cost associated to the length of edges which in turn has dramatic effects on the topological structure of these networks.

We will expose thoroughly the current state of our understanding of how the spatial constraints affect the structure and properties of these networks.

We will review the most recent empirical observations and the most important models of spatial networks.

We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

Today I read a paper titled “Elementary epistemological features of machine intelligence”

The abstract is:
Theoretical analysis of machine intelligence (MI) is useful for defining a common platform in both theoretical and applied artificial intelligence (AI).

The goal of this paper is to set canonical definitions that can assist pragmatic research in both strong and weak AI.

Described epistemological features of machine intelligence include relationship between intelligent behavior, intelligent and unintelligent machine characteristics, observable and unobservable entities and classification of intelligence.

The paper also establishes algebraic definitions of efficiency and accuracy of MI tests as their quality measure.

The last part of the paper addresses the learning process with respect to the traditional epistemology and the epistemology of MI described here.

The proposed views on MI positively correlate to the Hegelian monistic epistemology and contribute towards amalgamating idealistic deliberations with the AI theory, particularly in a local frame of reference.