justin

Today I read a paper titled “Tracking Point of View in Narrative”

The abstract is:
Third-person fictional narrative text is composed not only of passages that objectively narrate events, but also of passages that present characters’ thoughts, perceptions, and inner states.

Such passages take a character’s “psychological point of view”.

A language understander must determine the current psychological point of view in order to distinguish the beliefs of the characters from the facts of the story, to correctly attribute beliefs and other attitudes to their sources, and to understand the discourse relations among sentences.

Tracking the psychological point of view is not a trivial problem, because many sentences are not explicitly marked for point of view, and whether the point of view of a sentence is objective or that of a character (and if the latter, which character it is) often depends on the context in which the sentence appears.

Tracking the psychological point of view is the problem addressed in this work.

The approach is to seek, by extensive examinations of naturally-occurring narrative, regularities in the ways that authors manipulate point of view, and to develop an algorithm that tracks point of view on the basis of the regularities found.

This paper presents this algorithm, gives demonstrations of an implemented system, and describes the results of some preliminary empirical studies, which lend support to the algorithm..

Today I read a paper titled “Lighting Control using Pressure-Sensitive Touchpads”

The abstract is:
We introduce a novel approach to control physical lighting parameters by means of a pressure-sensitive touchpad.

The two-dimensional area of the touchpad is subdivided into 5 virtual sliders, each controlling the intensity of a color (red, green, blue, yellow, and white).

The physical interaction methodology is modeled directly after ubiquitous mechanical sliders and dimmers which tend to be used for intensity/volume control.

Our abstraction to a pressure-sensitive touchpad provides advantages and introduces additional benefits over such existing devices.

Today I read a paper titled “Detecting User Engagement in Everyday Conversations”

The abstract is:
This paper presents a novel application of speech emotion recognition: estimation of the level of conversational engagement between users of a voice communication system.

We begin by using machine learning techniques, such as the support vector machine (SVM), to classify users’ emotions as expressed in individual utterances.

However, this alone fails to model the temporal and interactive aspects of conversational engagement.

We therefore propose the use of a multilevel structure based on coupled hidden Markov models (HMM) to estimate engagement levels in continuous natural speech.

The first level is comprised of SVM-based classifiers that recognize emotional states, which could be (e.g.) discrete emotion types or arousal/valence levels.

A high-level HMM then uses these emotional states as input, estimating users’ engagement in conversation by decoding the internal states of the HMM.

We report experimental results obtained by applying our algorithms to the LDC Emotional Prosody and CallFriend speech corpora.

Today I read a paper titled “Utilitarian resource assignment”

The abstract is:
This paper studies a resource allocation problem introduced by Koutsoupias and Papadimitriou.

The scenario is modelled as a multiple-player game in which each player selects one of a finite number of known resources.

The cost to the player is the total weight of all players who choose that resource, multiplied by the “delay” of that resource.

Recent papers have studied the Nash equilibria and social optima of this game in terms of the $L_\infty$ cost metric, in which the social cost is taken to be the maximum cost to any player.

We study the $L_1$ variant of this game, in which the social cost is taken to be the sum of the costs to the individual players, rather than the maximum of these costs.

We give bounds on the size of the coordination ratio, which is the ratio between the social cost incurred by selfish behavior and the optimal social cost; we also study the algorithmic problem of finding optimal (lowest-cost) assignments and Nash Equilibria.

Additionally, we obtain bounds on the ratio between alternative Nash equilibria for some special cases of the problem.

Today I read a paper titled “Hybrid Rounding Techniques for Knapsack Problems”

The abstract is:
We address the classical knapsack problem and a variant in which an upper bound is imposed on the number of items that can be selected.

We show that appropriate combinations of rounding techniques yield novel and powerful ways of rounding.

As an application of these techniques, we present a linear-storage Polynomial Time Approximation Scheme (PTAS) and a Fully Polynomial Time Approximation Scheme (FPTAS) that compute an approximate solution, of any fixed accuracy, in linear time.

This linear complexity bound gives a substantial improvement of the best previously known polynomial bounds.

Today I read a paper titled “New security and control protocol for VoIP based on steganography and digital watermarking”

The abstract is:
In this paper new security and control protocol for Voice over Internet Protocol (VoIP) service is presented.

It is the alternative for the IETF’s (Internet Engineering Task Force) RTCP (Real-Time Control Protocol) for real-time application’s traffic.

Additionally this solution offers authentication and integrity, it is capable of exchanging and verifying QoS and security parameters.

It is based on digital watermarking and steganography that is why it does not consume additional bandwidth and the data transmitted is inseparably bound to the voice content.

Today I read a paper titled “Memory Efficient Arithmetic”

The abstract is:
In this paper we give an algorithm for computing the mth base-b digit (m=1 is the least significant digit) of an integer n (actually, it finds sharp approximations to n/b^m mod 1), where n is defined as the last number in a sequence of integers s1,s2,…,sL=n, where s1=0, s2=1, and each successive si is either the sum, product, or difference of two previous sj’s in the sequence.

In many cases, the algorithm will find this mth digit using far less memory than it takes to write down all the base-b digits of n, while the number of bit operations will grow only slighly worse than linear in the number of digits.

One consequence of this result is that the mth base-10 digit of 2^t can be found using O(t^{2/3} log^C t) bits of storage (for some C>0), and O(t log^C t) bit operations.

The algorithm is also highly parallelizable, and an M-fold reduction in running time can be achieved using M processors, although the memory required will then grow by a factor of M.

Today I read a paper titled “Selfish peering and routing in the Internet”

The abstract is:
The Internet is a loose amalgamation of independent service providers acting in their own self-interest.

We examine the implications of this economic reality on peering relationships.

Specifically, we consider how the incentives of the providers might determine where they choose to interconnect with each other.

We consider a game where two selfish network providers must establish peering points between their respective network graphs, given knowledge of traffic conditions and a nearest-exit routing policy for out-going traffic, as well as costs based on congestion and peering connectivity.

We focus on the pairwise stability equilibrium concept and use a stochastic procedure to solve for the stochastically pairwise stable configurations.

Stochastically stable networks are selected for their robustness to deviations in strategy and are therefore posited as the more likely networks to emerge in a dynamic setting.

We note a paucity of stochastically stable peering configurations under asymmetric conditions, particularly to unequal interdomain traffic flow, with adverse effects on system-wide efficiency.

Under bilateral flow conditions, we find that as the cost associated with the establishment of peering links approaches zero, the variance in the number of peering links of stochastically pairwise stable equilibria increases dramatically.

Today I read a paper titled “Generating Conditional Probabilities for Bayesian Networks: Easing the Knowledge Acquisition Problem”

The abstract is:
The number of probability distributions required to populate a conditional probability table (CPT) in a Bayesian network, grows exponentially with the number of parent-nodes associated with that table.

If the table is to be populated through knowledge elicited from a domain expert then the sheer magnitude of the task forms a considerable cognitive barrier.

In this paper we devise an algorithm to populate the CPT while easing the extent of knowledge acquisition.

The input to the algorithm consists of a set of weights that quantify the relative strengths of the influences of the parent-nodes on the child-node, and a set of probability distributions the number of which grows only linearly with the number of associated parent-nodes.

These are elicited from the domain expert.

The set of probabilities are obtained by taking into consideration the heuristics that experts use while arriving at probabilistic estimations.

The algorithm is used to populate the CPT by computing appropriate weighted sums of the elicited distributions.

We invoke the methods of information geometry to demonstrate how these weighted sums capture the expert’s judgemental strategy.

Today I read a paper titled “Analytic Definition of Curves and Surfaces by Parabolic Blending”

The abstract is:
A procedure for interpolating between specified points of a curve or surface is described.

The method guarantees slope continuity at all junctions.

A surface panel divided into p x q contiguous patches is completely specified by the coordinates of (p+1) x (q+1) points.

Each individual patch, however, depends parametrically on the coordinates of 16 points, allowing shape flexibility and global conformity.

Today I read a paper titled “The Best Trail Algorithm for Assisted Navigation of Web Sites”

The abstract is:
We present an algorithm called the Best Trail Algorithm, which helps solve the hypertext navigation problem by automating the construction of memex-like trails through the corpus.

The algorithm performs a probabilistic best-first expansion of a set of navigation trees to find relevant and compact trails.

We describe the implementation of the algorithm, scoring methods for trails, filtering algorithms and a new metric called \emph{potential gain} which measures the potential of a page for future navigation opportunities.

Today I read a paper titled “Learning in Multiagent Systems: An Introduction from a Game-Theoretic Perspective”

The abstract is:
We introduce the topic of learning in multiagent systems.

We first provide a quick introduction to the field of game theory, focusing on the equilibrium concepts of iterated dominance, and Nash equilibrium.

We show some of the most relevant findings in the theory of learning in games, including theorems on fictitious play, replicator dynamics, and evolutionary stable strategies.

The CLRI theory and n-level learning agents are introduced as attempts to apply some of these findings to the problem of engineering multiagent systems with learning agents.

Finally, we summarize some of the remaining challenges in the field of learning in multiagent systems.

Today I read a paper titled “What Is Working Memory and Mental Imagery? A Robot that Learns to Perform Mental Computations”

The abstract is:
This paper goes back to Turing (1936) and treats his machine as a cognitive model (W,D,B), where W is an “external world” represented by memory device (the tape divided into squares), and (D,B) is a simple robot that consists of the sensory-motor devices, D, and the brain, B.

The robot’s sensory-motor devices (the “eye”, the “hand”, and the “organ of speech”) allow the robot to simulate the work of any Turing machine.

The robot simulates the internal states of a Turing machine by “talking to itself.” At the stage of training, the teacher forces the robot (by acting directly on its motor centers) to perform several examples of an algorithm with different input data presented on tape.

Two effects are achieved: 1) The robot learns to perform the shown algorithm with any input data using the tape.

2) The robot learns to perform the algorithm “mentally” using an “imaginary tape.” The model illustrates the simplest concept of a universal learning neurocomputer, demonstrates universality of associative learning as the mechanism of programming, and provides a simplified, but nontrivial neurobiologically plausible explanation of the phenomena of working memory and mental imagery.

The model is implemented as a user-friendly program for Windows called EROBOT.

The program is available at www.brain0.com/software.html.