Unnamed: 0 int64 0 41k | title stringlengths 4 274 | category stringlengths 5 18 | summary stringlengths 22 3.66k | theme stringclasses 8
values |
|---|---|---|---|---|
9,000 | The IBM 2016 Speaker Recognition System | cs.SD | In this paper we describe the recent advancements made in the IBM i-vector
speaker recognition system for conversational speech. In particular, we
identify key techniques that contribute to significant improvements in
performance of our system, and quantify their contributions. The techniques
include: 1) a nearest-neig... | computer science |
9,001 | Data Cleaning for XML Electronic Dictionaries via Statistical Anomaly
Detection | cs.DB | Many important forms of data are stored digitally in XML format. Errors can
occur in the textual content of the data in the fields of the XML. Fixing these
errors manually is time-consuming and expensive, especially for large amounts
of data. There is increasing interest in the research, development, and use of
automat... | computer science |
9,002 | Semantic Properties of Customer Sentiment in Tweets | cs.CL | An increasing number of people are using online social networking services
(SNSs), and a significant amount of information related to experiences in
consumption is shared in this new media form. Text mining is an emerging
technique for mining useful information from the web. We aim at discovering in
particular tweets s... | computer science |
9,003 | "Did I Say Something Wrong?" A Word-Level Analysis of Wikipedia Articles
for Deletion Discussions | cs.CL | This thesis focuses on gaining linguistic insights into textual discussions
on a word level. It was of special interest to distinguish messages that
constructively contribute to a discussion from those that are detrimental to
them. Thereby, we wanted to determine whether "I"- and "You"-messages are
indicators for eithe... | computer science |
9,004 | The IBM Speaker Recognition System: Recent Advances and Error Analysis | cs.CL | We present the recent advances along with an error analysis of the IBM
speaker recognition system for conversational speech. Some of the key
advancements that contribute to our system include: a nearest-neighbor
discriminant analysis (NDA) approach (as opposed to LDA) for intersession
variability compensation in the i-... | computer science |
9,005 | Temporal Topic Modeling to Assess Associations between News Trends and
Infectious Disease Outbreaks | cs.SI | In retrospective assessments, internet news reports have been shown to
capture early reports of unknown infectious disease transmission prior to
official laboratory confirmation. In general, media interest and reporting
peaks and wanes during the course of an outbreak. In this study, we quantify
the extent to which med... | computer science |
9,006 | Predicting and Understanding Law-Making with Word Vectors and an
Ensemble Model | cs.CL | Out of nearly 70,000 bills introduced in the U.S. Congress from 2001 to 2015,
only 2,513 were enacted. We developed a machine learning approach to
forecasting the probability that any bill will become law. Starting in 2001
with the 107th Congress, we trained models on data from previous Congresses,
predicted all bills ... | computer science |
9,007 | Viewpoint and Topic Modeling of Current Events | cs.CL | There are multiple sides to every story, and while statistical topic models
have been highly successful at topically summarizing the stories in corpora of
text documents, they do not explicitly address the issue of learning the
different sides, the viewpoints, expressed in the documents. In this paper, we
show how thes... | computer science |
9,008 | The Intelligent Voice 2016 Speaker Recognition System | cs.SD | This paper presents the Intelligent Voice (IV) system submitted to the NIST
2016 Speaker Recognition Evaluation (SRE). The primary emphasis of SRE this
year was on developing speaker recognition technology which is robust for novel
languages that are much more heterogeneous than those used in the current
state-of-the-a... | computer science |
9,009 | Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm | stat.ML | In topic modeling, many algorithms that guarantee identifiability of the
topics have been developed under the premise that there exist anchor words --
i.e., words that only appear (with positive probability) in one topic.
Follow-up work has resorted to three or higher-order statistics of the data
corpus to relax the an... | computer science |
9,010 | DyNet: The Dynamic Neural Network Toolkit | stat.ML | We describe DyNet, a toolkit for implementing neural network models based on
dynamic declaration of network structure. In the static declaration strategy
that is used in toolkits like Theano, CNTK, and TensorFlow, the user first
defines a computation graph (a symbolic representation of the computation), and
then exampl... | computer science |
9,011 | Modelling dependency completion in sentence comprehension as a Bayesian
hierarchical mixture process: A case study involving Chinese relative clauses | stat.AP | We present a case-study demonstrating the usefulness of Bayesian hierarchical
mixture modelling for investigating cognitive processes. In sentence
comprehension, it is widely assumed that the distance between linguistic
co-dependents affects the latency of dependency resolution: the longer the
distance, the longer the ... | computer science |
9,012 | Consistent Alignment of Word Embedding Models | cs.CL | Word embedding models offer continuous vector representations that can
capture rich contextual semantics based on their word co-occurrence patterns.
While these word vectors can provide very effective features used in many NLP
tasks such as clustering similar words and inferring learning relationships,
many challenges ... | computer science |
9,013 | Feature overwriting as a finite mixture process: Evidence from
comprehension data | stat.ML | The ungrammatical sentence "The key to the cabinets are on the table" is
known to lead to an illusion of grammaticality. As discussed in the
meta-analysis by Jaeger et al., 2017, faster reading times are observed at the
verb are in the agreement-attraction sentence above compared to the equally
ungrammatical sentence "... | computer science |
9,014 | Representation Learning and Pairwise Ranking for Implicit Feedback in
Recommendation Systems | stat.ML | In this paper, we propose a novel ranking framework for collaborative
filtering with the overall aim of learning user preferences over items by
minimizing a pairwise ranking loss. We show the minimization problem involves
dependent random variables and provide a theoretical analysis by proving the
consistency of the em... | computer science |
9,015 | Fuzzy Approach Topic Discovery in Health and Medical Corpora | stat.ML | The majority of medical documents and electronic health records (EHRs) are in
text format that poses a challenge for data processing and finding relevant
documents. Looking for ways to automatically retrieve the enormous amount of
health and medical knowledge has always been an intriguing topic. Powerful
methods have b... | computer science |
9,016 | A network approach to topic models | stat.ML | One of the main computational and scientific challenges in the modern age is
to extract useful information from unstructured texts. Topic models are one
popular machine-learning approach which infers the latent topical structure of
a collection of documents. Despite their success --- in particular of its most
widely us... | computer science |
9,017 | Database of Parliamentary Speeches in Ireland, 1919-2013 | cs.CL | We present a database of parliamentary debates that contains the complete
record of parliamentary speeches from D\'ail \'Eireann, the lower house and
principal chamber of the Irish parliament, from 1919 to 2013. In addition, the
database contains background information on all TDs (Teachta D\'ala, members of
parliament)... | computer science |
9,018 | Speech recognition for medical conversations | cs.CL | In this paper we document our experiences with developing speech recognition
for medical transcription - a system that automatically transcribes
doctor-patient conversations. Towards this goal, we built a system along two
different methodological lines - a Connectionist Temporal Classification (CTC)
phoneme based model... | computer science |
9,019 | Language Bootstrapping: Learning Word Meanings From Perception-Action
Association | cs.RO | We address the problem of bootstrapping language acquisition for an
artificial system similarly to what is observed in experiments with human
infants. Our method works by associating meanings to words in manipulation
tasks, as a robot interacts with objects and listens to verbal descriptions of
the interactions. The mo... | computer science |
9,020 | State-of-the-art Speech Recognition With Sequence-to-Sequence Models | cs.CL | Attention-based encoder-decoder architectures such as Listen, Attend, and
Spell (LAS), subsume the acoustic, pronunciation and language model components
of a traditional automatic speech recognition (ASR) system into a single neural
network. In previous work, we have shown that such architectures are comparable
to stat... | computer science |
9,021 | Improving the Performance of Online Neural Transducer Models | cs.CL | Having a sequence-to-sequence model which can operate in an online fashion is
important for streaming applications such as Voice Search. Neural transducer is
a streaming sequence-to-sequence model, but has shown a significant degradation
in performance compared to non-streaming models such as Listen, Attend and
Spell (... | computer science |
9,022 | Minimum Word Error Rate Training for Attention-based
Sequence-to-Sequence Models | cs.CL | Sequence-to-sequence models, such as attention-based models in automatic
speech recognition (ASR), are typically trained to optimize the cross-entropy
criterion which corresponds to improving the log-likelihood of the data.
However, system performance is usually measured in terms of word error rate
(WER), not log-likel... | computer science |
9,023 | No Need for a Lexicon? Evaluating the Value of the Pronunciation Lexica
in End-to-End Models | cs.CL | For decades, context-dependent phonemes have been the dominant sub-word unit
for conventional acoustic modeling systems. This status quo has begun to be
challenged recently by end-to-end models which seek to combine acoustic,
pronunciation, and language model components into a single neural network. Such
systems, which... | computer science |
9,024 | Characterizing Political Fake News in Twitter by its Meta-Data | cs.CL | This article presents a preliminary approach towards characterizing political
fake news on Twitter through the analysis of their meta-data. In particular, we
focus on more than 1.5M tweets collected on the day of the election of Donald
Trump as 45th president of the United States of America. We use the meta-data
embedd... | computer science |
9,025 | Multilingual Topic Models | stat.ML | Scientific publications have evolved several features for mitigating
vocabulary mismatch when indexing, retrieving, and computing similarity between
articles. These mitigation strategies range from simply focusing on high-value
article sections, such as titles and abstracts, to assigning keywords, often
from controlled... | computer science |
9,026 | Improving End-to-End Speech Recognition with Policy Learning | cs.CL | Connectionist temporal classification (CTC) is widely used for maximum
likelihood learning in end-to-end speech recognition models. However, there is
usually a disparity between the negative maximum likelihood and the performance
metric used in speech recognition, e.g., word error rate (WER). This results in
a mismatch... | computer science |
9,027 | Improved Regularization Techniques for End-to-End Speech Recognition | cs.CL | Regularization is important for end-to-end speech models, since the models
are highly flexible and easy to overfit. Data augmentation and dropout has been
important for improving end-to-end models in other domains. However, they are
relatively under explored for end-to-end speech models. Therefore, we
investigate the e... | computer science |
9,028 | Cross-type Biomedical Named Entity Recognition with Deep Multi-Task
Learning | cs.IR | Motivation: Biomedical named entity recognition (BioNER) is the most
fundamental task in biomedical text mining. State-of-the-art BioNER systems
often require handcrafted features specifically designed for each type of
biomedical entities. This feature generation process requires intensive labors
from biomedical and li... | computer science |
9,029 | How to Make Causal Inferences Using Texts | stat.ML | New text as data techniques offer a great promise: the ability to inductively
discover measures that are useful for testing social science theories of
interest from large collections of text. We introduce a conceptual framework
for making causal inferences with discovered measures as a treatment or
outcome. Our framewo... | computer science |
9,030 | Can we steal your vocal identity from the Internet?: Initial
investigation of cloning Obama's voice using GAN, WaveNet and low-quality
found data | eess.AS | Thanks to the growing availability of spoofing databases and rapid advances
in using them, systems for detecting voice spoofing attacks are becoming more
and more capable, and error rates close to zero are being reached for the
ASVspoof2015 database. However, speech synthesis and voice conversion paradigms
that are not... | computer science |
9,031 | A Neural Network Assembly Memory Model with Maximum-Likelihood Recall
and Recognition Properties | cs.AI | It has been shown that a neural network model recently proposed to describe
basic memory performance is based on a ternary/binary coding/decoding algorithm
which leads to a new neural network assembly memory model (NNAMM) providing
maximum-likelihood recall/recognition properties and implying a new memory unit
architec... | computer science |
9,032 | A Neural Network Assembly Memory Model Based on an Optimal Binary Signal
Detection Theory | cs.AI | A ternary/binary data coding algorithm and conditions under which Hopfield
networks implement optimal convolutional or Hamming decoding algorithms has
been described. Using the coding/decoding approach (an optimal Binary Signal
Detection Theory, BSDT) introduced a Neural Network Assembly Memory Model
(NNAMM) is built. ... | computer science |
9,033 | TRUST-TECH based Methods for Optimization and Learning | cs.AI | Many problems that arise in machine learning domain deal with nonlinearity
and quite often demand users to obtain global optimal solutions rather than
local optimal ones. Optimization problems are inherent in machine learning
algorithms and hence many methods in machine learning were inherited from the
optimization lit... | computer science |
9,034 | Schema Redescription in Cellular Automata: Revisiting Emergence in
Complex Systems | nlin.CG | We present a method to eliminate redundancy in the transition tables of
Boolean automata: schema redescription with two symbols. One symbol is used to
capture redundancy of individual input variables, and another to capture
permutability in sets of input variables: fully characterizing the canalization
present in Boole... | computer science |
9,035 | Motility at the origin of life: Its characterization and a model | cs.AI | Due to recent advances in synthetic biology and artificial life, the origin
of life is currently a hot topic of research. We review the literature and
argue that the two traditionally competing "replicator-first" and
"metabolism-first" approaches are merging into one integrated theory of
individuation and evolution. We... | computer science |
9,036 | A Consumer BCI for Automated Music Evaluation Within a Popular On-Demand
Music Streaming Service - Taking Listener's Brainwaves to Extremes | cs.AI | We investigated the possibility of using a machine-learning scheme in
conjunction with commercial wearable EEG-devices for translating listener's
subjective experience of music into scores that can be used for the automated
annotation of music in popular on-demand streaming services. Based on the
established -neuroscie... | computer science |
9,037 | The Impact of Coevolution and Abstention on the Emergence of Cooperation | cs.GT | This paper explores the Coevolutionary Optional Prisoner's Dilemma (COPD)
game, which is a simple model to coevolve game strategy and link weights of
agents playing the Optional Prisoner's Dilemma game. We consider a population
of agents placed in a lattice grid with boundary conditions. A number of Monte
Carlo simulat... | computer science |
9,038 | Deep Predictive Models in Interactive Music | cs.SD | Automatic music generation is a compelling task where much recent progress
has been made with deep learning models. In this paper, we ask how these models
can be integrated into interactive music systems; how can they encourage or
enhance the music making of human users? Musical performance requires
prediction to opera... | computer science |
9,039 | On a cepstrum-based speech detector robust to white noise | cs.CL | We study effects of additive white noise on the cepstral representation of
speech signals. Distribution of each individual cepstrum coefficient of speech
is shown to depend strongly on noise and to overlap significantly with the
cepstrum distribution of noise. Based on these studies, we suggest a scalar
quantity, V, eq... | computer science |
9,040 | Discrimination between Arabic and Latin from bilingual documents | cs.CV | 2011 International Conference on Communications, Computing and Control
Applications (CCCA) | computer science |
9,041 | Arabic Text Recognition in Video Sequences | cs.MM | In this paper, we propose a robust approach for text extraction and
recognition from Arabic news video sequence. The text included in video
sequences is an important needful for indexing and searching system. However,
this text is difficult to detect and recognize because of the variability of
its size, their low resol... | computer science |
9,042 | Joint Video and Text Parsing for Understanding Events and Answering
Queries | cs.CV | We propose a framework for parsing video and text jointly for understanding
events and answering user queries. Our framework produces a parse graph that
represents the compositional structures of spatial information (objects and
scenes), temporal information (actions and events) and causal information
(causalities betw... | computer science |
9,043 | VideoSET: Video Summary Evaluation through Text | cs.CV | In this paper we present VideoSET, a method for Video Summary Evaluation
through Text that can evaluate how well a video summary is able to retain the
semantic information contained in its original video. We observe that semantics
is most easily expressed in words, and develop a text-based approach for the
evaluation. ... | computer science |
9,044 | Spectral Analysis of Projection Histogram for Enhancing Close matching
character Recognition in Malayalam | cs.CL | The success rates of Optical Character Recognition (OCR) systems for printed
Malayalam documents is quite impressive with the state of the art accuracy
levels in the range of 85-95% for various. However for real applications,
further enhancement of this accuracy levels are required. One of the bottle
necks in further e... | computer science |
9,045 | Saying What You're Looking For: Linguistics Meets Video Search | cs.CV | We present an approach to searching large video corpora for video clips which
depict a natural-language query in the form of a sentence. This approach uses
compositional semantics to encode subtle meaning that is lost in other systems,
such as the difference between two sentences which have identical words but
entirely... | computer science |
9,046 | Image Captioning with Deep Bidirectional LSTMs | cs.CV | This work presents an end-to-end trainable deep bidirectional LSTM
(Long-Short Term Memory) model for image captioning. Our model builds on a deep
convolutional neural network (CNN) and two separate LSTM networks. It is
capable of learning long term visual-language interactions by making use of
history and future conte... | computer science |
9,047 | Video In Sentences Out | cs.CV | We present a system that produces sentential descriptions of video: who did
what to whom, and where and how they did it. Action class is rendered as a
verb, participant objects as noun phrases, properties of those objects as
adjectival modifiers in those noun phrases, spatial relations between those
participants as pre... | computer science |
9,048 | Web Similarity | cs.IR | Normalized web distance (NWD) is a similarity or normalized semantic distance
based on the World Wide Web or any other large electronic database, for
instance Wikipedia, and a search engine that returns reliable aggregate page
counts. For sets of search terms the NWD gives a similarity on a scale from 0
(identical) to ... | computer science |
9,049 | What's Cookin'? Interpreting Cooking Videos using Text, Speech and
Vision | cs.CL | We present a novel method for aligning a sequence of instructions to a video
of someone carrying out a task. In particular, we focus on the cooking domain,
where the instructions correspond to the recipe. Our technique relies on an HMM
to align the recipe steps to the (automatically generated) speech transcript.
We the... | computer science |
9,050 | CIDEr: Consensus-based Image Description Evaluation | cs.CV | Automatically describing an image with a sentence is a long-standing
challenge in computer vision and natural language processing. Due to recent
progress in object detection, attribute classification, action recognition,
etc., there is renewed interest in this area. However, evaluating the quality
of descriptions has p... | computer science |
9,051 | A Dataset for Movie Description | cs.CV | Descriptive video service (DVS) provides linguistic descriptions of movies
and allows visually impaired people to follow a movie along with their peers.
Such descriptions are by design mainly visual and thus naturally form an
interesting data source for computer vision and computational linguistics. In
this work we pro... | computer science |
9,052 | Visual Affect Around the World: A Large-scale Multilingual Visual
Sentiment Ontology | cs.MM | Every culture and language is unique. Our work expressly focuses on the
uniqueness of culture and language in relation to human affect, specifically
sentiment and emotion semantics, and how they manifest in social multimedia. We
develop sets of sentiment- and emotion-polarized visual concepts by adapting
semantic struc... | computer science |
9,053 | Selecting Relevant Web Trained Concepts for Automated Event Retrieval | cs.CV | Complex event retrieval is a challenging research problem, especially when no
training videos are available. An alternative to collecting training videos is
to train a large semantic concept bank a priori. Given a text description of an
event, event retrieval is performed by selecting concepts linguistically
related to... | computer science |
9,054 | Learning Articulated Motion Models from Visual and Lingual Signals | cs.RO | In order for robots to operate effectively in homes and workplaces, they must
be able to manipulate the articulated objects common within environments built
for and by humans. Previous work learns kinematic models that prescribe this
manipulation from visual demonstrations. Lingual signals, such as natural
language des... | computer science |
9,055 | Fine-Grain Annotation of Cricket Videos | cs.MM | The recognition of human activities is one of the key problems in video
understanding. Action recognition is challenging even for specific categories
of videos, such as sports, that contain only a small set of actions.
Interestingly, sports videos are accompanied by detailed commentaries available
online, which could b... | computer science |
9,056 | Learning the Semantics of Manipulation Action | cs.RO | In this paper we present a formal computational framework for modeling
manipulation actions. The introduced formalism leads to semantics of
manipulation action and has applications to both observing and understanding
human manipulation actions as well as executing them with a robotic mechanism
(e.g. a humanoid robot). ... | computer science |
9,057 | Neural Self Talk: Image Understanding via Continuous Questioning and
Answering | cs.CV | In this paper we consider the problem of continuously discovering image
contents by actively asking image based questions and subsequently answering
the questions being asked. The key components include a Visual Question
Generation (VQG) module and a Visual Question Answering module, in which
Recurrent Neural Networks ... | computer science |
9,058 | openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words
Toolkit | cs.CV | We introduce openXBOW, an open-source toolkit for the generation of
bag-of-words (BoW) representations from multimodal input. In the BoW principle,
word histograms were first used as features in document classification, but the
idea was and can easily be adapted to, e.g., acoustic or visual low-level
descriptors, intro... | computer science |
9,059 | Going Deeper for Multilingual Visual Sentiment Detection | cs.MM | This technical report details several improvements to the visual concept
detector banks built on images from the Multilingual Visual Sentiment Ontology
(MVSO). The detector banks are trained to detect a total of 9,918
sentiment-biased visual concepts from six major languages: English, Spanish,
Italian, French, German a... | computer science |
9,060 | Multilingual Visual Sentiment Concept Matching | cs.CL | The impact of culture in visual emotion perception has recently captured the
attention of multimedia research. In this study, we pro- vide powerful
computational linguistics tools to explore, retrieve and browse a dataset of
16K multilingual affective visual concepts and 7.3M Flickr images. First, we
design an effectiv... | computer science |
9,061 | Detecting Sarcasm in Multimodal Social Platforms | cs.CV | Sarcasm is a peculiar form of sentiment expression, where the surface
sentiment differs from the implied sentiment. The detection of sarcasm in
social media platforms has been applied in the past mainly to textual
utterances where lexical indicators (such as interjections and intensifiers),
linguistic markers, and cont... | computer science |
9,062 | Open-Ended Visual Question-Answering | cs.CL | This thesis report studies methods to solve Visual Question-Answering (VQA)
tasks with a Deep Learning framework. As a preliminary step, we explore Long
Short-Term Memory (LSTM) networks used in Natural Language Processing (NLP) to
tackle Question-Answering (text based). We then modify the previous model to
accept an i... | computer science |
9,063 | Attention-Based Multimodal Fusion for Video Description | cs.CV | Currently successful methods for video description are based on
encoder-decoder sentence generation using recur-rent neural networks (RNNs).
Recent work has shown the advantage of integrating temporal and/or spatial
attention mechanisms into these models, in which the decoder net-work predicts
each word in the descript... | computer science |
9,064 | Cats and Captions vs. Creators and the Clock: Comparing Multimodal
Content to Context in Predicting Relative Popularity | cs.SI | The content of today's social media is becoming more and more rich,
increasingly mixing text, images, videos, and audio. It is an intriguing
research question to model the interplay between these different modes in
attracting user attention and engagement. But in order to pursue this study of
multimodal content, we mus... | computer science |
9,065 | Query-adaptive Video Summarization via Quality-aware Relevance
Estimation | cs.CV | Although the problem of automatic video summarization has recently received a
lot of attention, the problem of creating a video summary that also highlights
elements relevant to a search query has been less studied. We address this
problem by posing query-relevant summarization as a video frame subset
selection problem... | computer science |
9,066 | FOIL it! Find One mismatch between Image and Language caption | cs.CV | In this paper, we aim to understand whether current language and vision
(LaVi) models truly grasp the interaction between the two modalities. To this
end, we propose an extension of the MSCOCO dataset, FOIL-COCO, which associates
images with both correct and "foil" captions, that is, descriptions of the
image that are ... | computer science |
9,067 | Modality-specific Cross-modal Similarity Measurement with Recurrent
Attention Network | cs.CV | Nowadays, cross-modal retrieval plays an indispensable role to flexibly find
information across different modalities of data. Effectively measuring the
similarity between different modalities of data is the key of cross-modal
retrieval. Different modalities such as image and text have imbalanced and
complementary relat... | computer science |
9,068 | Updating the silent speech challenge benchmark with deep learning | cs.CL | The 2010 Silent Speech Challenge benchmark is updated with new results
obtained in a Deep Learning strategy, using the same input features and
decoding strategy as in the original article. A Word Error Rate of 6.4% is
obtained, compared to the published value of 17.4%. Additional results
comparing new auto-encoder-base... | computer science |
9,069 | Object Referring in Visual Scene with Spoken Language | cs.CV | Object referring has important applications, especially for human-machine
interaction. While having received great attention, the task is mainly attacked
with written language (text) as input rather than spoken language (speech),
which is more natural. This paper investigates Object Referring with Spoken
Language (ORSp... | computer science |
9,070 | Visual and Textual Sentiment Analysis Using Deep Fusion Convolutional
Neural Networks | cs.CL | Sentiment analysis is attracting more and more attentions and has become a
very hot research topic due to its potential applications in personalized
recommendation, opinion mining, etc. Most of the existing methods are based on
either textual or visual data and can not achieve satisfactory results, as it
is very hard t... | computer science |
9,071 | Deep Inference of Personality Traits by Integrating Image and Word Use
in Social Networks | cs.CY | Social media, as a major platform for communication and information exchange,
is a rich repository of the opinions and sentiments of 2.3 billion users about
a vast spectrum of topics. To sense the whys of certain social user's demands
and cultural-driven interests, however, the knowledge embedded in the 1.8
billion pic... | computer science |
9,072 | VizWiz Grand Challenge: Answering Visual Questions from Blind People | cs.CV | The study of algorithms to automatically answer visual questions currently is
motivated by visual question answering (VQA) datasets constructed in artificial
VQA settings. We propose VizWiz, the first goal-oriented VQA dataset arising
from a natural VQA setting. VizWiz consists of over 31,000 visual questions
originati... | computer science |
9,073 | Multimodal Sentiment Analysis: Addressing Key Issues and Setting up
Baselines | cs.CL | Sentiment analysis is proven to be very useful tool in many applications
regarding social media. This has led to a great surge of research in this
field. Hence, in this paper, we compile the baselines for such research. In
this paper, we explore three different deep-learning based architectures for
multimodal sentiment... | computer science |
9,074 | The ILIUM forward modelling algorithm for multivariate parameter
estimation and its application to derive stellar parameters from Gaia
spectrophotometry | cs.NE | I introduce an algorithm for estimating parameters from multidimensional data
based on forward modelling. In contrast to many machine learning approaches it
avoids fitting an inverse model and the problems associated with this. The
algorithm makes explicit use of the sensitivities of the data to the
parameters, with th... | computer science |
9,075 | Financial Portfolio Optimization: Computationally guided agents to
investigate, analyse and invest!? | cs.CE | Financial portfolio optimization is a widely studied problem in mathematics,
statistics, financial and computational literature. It adheres to determining
an optimal combination of weights associated with financial assets held in a
portfolio. In practice, it faces challenges by virtue of varying math.
formulations, par... | computer science |
9,076 | Stochastic inference with deterministic spiking neurons | cs.NE | The seemingly stochastic transient dynamics of neocortical circuits observed
in vivo have been hypothesized to represent a signature of ongoing stochastic
inference. In vitro neurons, on the other hand, exhibit a highly deterministic
response to various types of stimulation. We show that an ensemble of
deterministic le... | computer science |
9,077 | Dimension of Marginals of Kronecker Product Models | stat.ML | A Kronecker product model is the set of visible marginal probability
distributions of an exponential family whose sufficient statistics matrix
factorizes as a Kronecker product of two matrices, one for the visible
variables and one for the hidden variables. We estimate the dimension of these
models by the maximum rank ... | computer science |
9,078 | Linear Readout of Object Manifolds | cs.NE | Objects are represented in sensory systems by continuous manifolds due to
sensitivity of neuronal responses to changes in physical features such as
location, orientation, and intensity. What makes certain sensory
representations better suited for invariant decoding of objects by downstream
networks? We present a theory... | computer science |
9,079 | The high-conductance state enables neural sampling in networks of LIF
neurons | cs.NE | The apparent stochasticity of in-vivo neural circuits has long been
hypothesized to represent a signature of ongoing stochastic inference in the
brain. More recently, a theoretical framework for neural sampling has been
proposed, which explains how sample-based inference can be performed by
networks of spiking neurons.... | computer science |
9,080 | Stochastic inference with spiking neurons in the high-conductance state | cs.NE | The highly variable dynamics of neocortical circuits observed in vivo have
been hypothesized to represent a signature of ongoing stochastic inference but
stand in apparent contrast to the deterministic response of neurons measured in
vitro. Based on a propagation of the membrane autocorrelation across spike
bursts, we ... | computer science |
9,081 | Classification and Geometry of General Perceptual Manifolds | cs.NE | Perceptual manifolds arise when a neural population responds to an ensemble
of sensory signals associated with different physical features (e.g.,
orientation, pose, scale, location, and intensity) of the same perceptual
object. Object recognition and discrimination requires classifying the
manifolds in a manner that is... | computer science |
9,082 | Machine Learning of User Profiles: Representational Issues | cs.CL | As more information becomes available electronically, tools for finding
information of interest to users becomes increasingly important. The goal of
the research described here is to build a system for generating comprehensible
user profiles that accurately capture user interest with minimum user
interaction. The resea... | computer science |
9,083 | Extended Comment on Language Trees and Zipping | cs.CL | This is the extended version of a Comment submitted to Physical Review
Letters. I first point out the inappropriateness of publishing a Letter
unrelated to physics. Next, I give experimental results showing that the
technique used in the Letter is 3 times worse and 17 times slower than a simple
baseline. And finally, I... | computer science |
9,084 | An Experimental Comparison of Naive Bayesian and Keyword-Based Anti-Spam
Filtering with Personal E-mail Messages | cs.CL | The growing problem of unsolicited bulk e-mail, also known as "spam", has
generated a need for reliable anti-spam e-mail filters. Filters of this type
have so far been based mostly on manually constructed keyword patterns. An
alternative approach has recently been proposed, whereby a Naive Bayesian
classifier is traine... | computer science |
9,085 | Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a
Memory-Based Approach | cs.CL | We investigate the performance of two machine learning algorithms in the
context of anti-spam filtering. The increasing volume of unsolicited bulk
e-mail (spam) has generated a need for reliable anti-spam filters. Filters of
this type have so far been based mostly on keyword patterns that are
constructed by hand and pe... | computer science |
9,086 | Coupled Clustering: a Method for Detecting Structural Correspondence | cs.LG | This paper proposes a new paradigm and computational framework for
identification of correspondences between sub-structures of distinct composite
systems. For this, we define and investigate a variant of traditional data
clustering, termed coupled clustering, which simultaneously identifies
corresponding clusters withi... | computer science |
9,087 | Learning Algorithms for Keyphrase Extraction | cs.LG | Many academic journals ask their authors to provide a list of about five to
fifteen keywords, to appear on the first page of each article. Since these key
words are often phrases of two or more words, we prefer to call them
keyphrases. There is a wide variety of tasks for which keyphrases are useful,
as we discuss in t... | computer science |
9,088 | Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised
Classification of Reviews | cs.LG | This paper presents a simple unsupervised learning algorithm for classifying
reviews as recommended (thumbs up) or not recommended (thumbs down). The
classification of a review is predicted by the average semantic orientation of
the phrases in the review that contain adjectives or adverbs. A phrase has a
positive seman... | computer science |
9,089 | Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL | cs.LG | This paper presents a simple unsupervised learning algorithm for recognizing
synonyms, based on statistical data acquired by querying a Web search engine.
The algorithm, called PMI-IR, uses Pointwise Mutual Information (PMI) and
Information Retrieval (IR) to measure the similarity of pairs of words. PMI-IR
is empirical... | computer science |
9,090 | Learning Analogies and Semantic Relations | cs.LG | We present an algorithm for learning from unlabeled text, based on the Vector
Space Model (VSM) of information retrieval, that can solve verbal analogy
questions of the kind found in the Scholastic Aptitude Test (SAT). A verbal
analogy has the form A:B::C:D, meaning "A is to B as C is to D"; for example,
mason:stone::c... | computer science |
9,091 | Coherent Keyphrase Extraction via Web Mining | cs.LG | Keyphrases are useful for a variety of purposes, including summarizing,
indexing, labeling, categorizing, clustering, highlighting, browsing, and
searching. The task of automatic keyphrase extraction is to select keyphrases
from within the text of a given document. Automatic keyphrase extraction makes
it feasible to ge... | computer science |
9,092 | Measuring Praise and Criticism: Inference of Semantic Orientation from
Association | cs.CL | The evaluative character of a word is called its semantic orientation.
Positive semantic orientation indicates praise (e.g., "honest", "intrepid") and
negative semantic orientation indicates criticism (e.g., "disturbing",
"superfluous"). Semantic orientation varies in both direction (positive or
negative) and degree (m... | computer science |
9,093 | Combining Independent Modules to Solve Multiple-choice Synonym and
Analogy Problems | cs.CL | Existing statistical approaches to natural language problems are very coarse
approximations to the true complexity of language processing. As such, no
single technique will be best for all problem instances. Many researchers are
examining ensemble methods that combine the output of successful, separately
developed modu... | computer science |
9,094 | Word Sense Disambiguation by Web Mining for Word Co-occurrence
Probabilities | cs.CL | This paper describes the National Research Council (NRC) Word Sense
Disambiguation (WSD) system, as applied to the English Lexical Sample (ELS)
task in Senseval-3. The NRC system approaches WSD as a classical supervised
machine learning problem, using familiar tools such as the Weka machine
learning software and Brill'... | computer science |
9,095 | Human-Level Performance on Word Analogy Questions by Latent Relational
Analysis | cs.CL | This paper introduces Latent Relational Analysis (LRA), a method for
measuring relational similarity. LRA has potential applications in many areas,
including information extraction, word sense disambiguation, machine
translation, and information retrieval. Relational similarity is correspondence
between relations, in c... | computer science |
9,096 | Combining Independent Modules in Lexical Multiple-Choice Problems | cs.LG | Existing statistical approaches to natural language problems are very coarse
approximations to the true complexity of language processing. As such, no
single technique will be best for all problem instances. Many researchers are
examining ensemble methods that combine the output of multiple modules to
create more accur... | computer science |
9,097 | Measuring Semantic Similarity by Latent Relational Analysis | cs.LG | This paper introduces Latent Relational Analysis (LRA), a method for
measuring semantic similarity. LRA measures similarity in the semantic
relations between two pairs of words. When two pairs have a high degree of
relational similarity, they are analogous. For example, the pair cat:meow is
analogous to the pair dog:ba... | computer science |
9,098 | Corpus-based Learning of Analogies and Semantic Relations | cs.LG | We present an algorithm for learning from unlabeled text, based on the Vector
Space Model (VSM) of information retrieval, that can solve verbal analogy
questions of the kind found in the SAT college entrance exam. A verbal analogy
has the form A:B::C:D, meaning "A is to B as C is to D"; for example,
mason:stone::carpen... | computer science |
9,099 | Similarity of Semantic Relations | cs.CL | There are at least two kinds of similarity. Relational similarity is
correspondence between relations, in contrast with attributional similarity,
which is correspondence between attributes. When two words have a high degree
of attributional similarity, we call them synonyms. When two pairs of words
have a high degree o... | computer science |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.