text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
|---|---|---|
of analysis of are for massive amounts their Therefore, applications the impractical. data | Therefore, their applications for the analysis of massive amounts of data are impractical. | 15,800 |
computations example, due For to data computationally are prohibitive. repeated accumulated | For example, repeated computations due to accumulated data are computationally prohibitive. | 15,801 |
extension newly-arrived points. out-of-sample an We algorithm to an data which describe performs | We describe an algorithm which performs an out-of-sample extension to newly-arrived data points. | 15,802 |
We the the prove is bounded. proposed of error algorithm that | We prove that the error of the proposed algorithm is bounded. | 15,803 |
The similar have points a four stage. evaluated successional | The four evaluated points have a similar successional stage. | 15,804 |
major on on shown two fronts. has Recent developments subtraction work background | Recent work on background subtraction has shown developments on two major fronts. | 15,805 |
model from frequencies is also studied. identifiability of The parameters $k$-mer | The identifiability of model parameters from $k$-mer frequencies is also studied. | 15,806 |
Medicago In this we model the explore issue truncatula. legume this using wild paper | In this paper we explore this issue using the wild model legume Medicago truncatula. | 15,807 |
biomedicine breeding insight and can accelerate This research programs. | This insight can accelerate breeding and biomedicine research programs. | 15,808 |
segmentation (FCNs). by in state-of-the-art networks currently The represented semantic convolutional is fully | The state-of-the-art in semantic segmentation is currently represented by fully convolutional networks (FCNs). | 15,809 |
FCNs result object boundaries. around a As are produce segmentations to tend localized that poorly | As a result FCNs tend to produce segmentations that are poorly localized around object boundaries. | 15,810 |
and segment coherence used is to The information boundary to localization. object semantic improve enhance | The boundary information is used to enhance semantic segment coherence and to improve object localization. | 15,811 |
pairwise the boundaries energy. then We to define employ in our predicted potentials | We then employ the predicted boundaries to define pairwise potentials in our energy. | 15,812 |
performance image tasks. its ConvNets have classification Deep shown in good | Deep ConvNets have shown its good performance in image classification tasks. | 15,813 |
deep a remains However as recognition. it representation still action for video problem in | However it still remains as a problem in deep video representation for action recognition. | 15,814 |
pooled the video to encoded then The VLAD with representations. descriptors form local are | The pooled local descriptors are then encoded with VLAD to form the video representations. | 15,815 |
performance object recall. on paper of terms in focus In improving we this detection | In this paper we focus on improving object detection performance in terms of recall. | 15,816 |
by the is sampling exploration performed This image. in proposals object | This exploration is performed by sampling object proposals in the image. | 15,817 |
we of propose In relations objects. method a between discover addition, to higher-order groups novel | In addition, we propose a novel method to discover higher-order relations between groups of objects. | 15,818 |
for In a scheme content we paper, intra propose this prediction screen video. novel | In this paper, we propose a novel intra prediction scheme for screen content video. | 15,819 |
We SR techniques (i.e. benchmarks validate our on seven standard | We validate our seven techniques on standard SR benchmarks (i.e. | 15,820 |
detection. a hand introduce new We for pipeline and fingertip localization | We introduce a new pipeline for hand localization and fingertip detection. | 15,821 |
cities. an ozone task is of modern prediction level agencies important air quality The of | The ozone level prediction is an important task of air quality agencies of modern cities. | 15,822 |
computer inputs based with propose output. We a system three single and | We propose a computer based system with three inputs and single output. | 15,823 |
with This computationally machines. focus the model capable Turing modularized view the the binds with | This modularized view with the focus binds the model with the computationally capable Turing machines. | 15,824 |
other related RAC mA+ relate contribute MADs. that we formalisms Finally, in to to | Finally, we relate mA+ to other related formalisms that contribute to RAC in MADs. | 15,825 |
detect Moreover, to identification might be hard constraints statistically. | Moreover, identification constraints might be hard to detect statistically. | 15,826 |
prove on the bounds of We OA in an patterns model. properties theoretical | We prove theoretical bounds on the properties of patterns in an OA model. | 15,827 |
degree differences explained. the were Then, proposed moving existing and rate between matching | Then, the differences between proposed moving rate and existing matching degree were explained. | 15,828 |
proposed T-S model. method identification based rate the for moving is Next, on | Next, the identification method based on moving rate is proposed for T-S model. | 15,829 |
that significantly Test fuzzy identification. of proposed improves results show method effectiveness the the | Test results show that the proposed method significantly improves the effectiveness of fuzzy identification. | 15,830 |
we neutrality theoretical derive the on Within NERM risks. bound a empirical generalization and framework, | Within the NERM framework, we derive a theoretical bound on empirical and generalization neutrality risks. | 15,831 |
problem. method This attractiveness the address a prediction to paper proposes leaning challenging deep facial | This paper proposes a deep leaning method to address the challenging facial attractiveness prediction problem. | 15,832 |
unresolved been developed limitations proposed, remain. issues have and several certain and Although methods | Although several methods have been developed and proposed, certain limitations and unresolved issues remain. | 15,833 |
Different or measures have vectors. applied similarity these been dissimilarity to | Different similarity or dissimilarity measures have been applied to these vectors. | 15,834 |
are their and advantages Specifically, disadvantages compared. mentioned and | Specifically, their advantages and disadvantages are mentioned and compared. | 15,835 |
adding the model capacity competition WTA neurons. information hidden of The increases the without | The WTA competition increases the information capacity of the model without adding hidden neurons. | 15,836 |
Logo intellectual and recognition applications, for brand protection. particularly from has property detection many images | Logo detection from images has many applications, particularly for brand recognition and intellectual property protection. | 15,837 |
and describe a database. constructing ideas for large-scale the such We challenges | We describe the ideas and challenges for constructing such a large-scale database. | 15,838 |
neuroscientific research humans objects. demonstrates fixed size a Recent salient have for prior that | Recent neuroscientific research demonstrates that humans have a fixed size prior for salient objects. | 15,839 |
available source All pre-trained will at be and models GitHub. code | All source code and pre-trained models will be available at GitHub. | 15,840 |
The calculation only advantage the has that simulations is to over executed once. be | The advantage over simulations is that the calculation has to be executed only once. | 15,841 |
the matrix is Building automated algorithm. transition our by | Building the transition matrix is automated by our algorithm. | 15,842 |
on a paper perform analysis we In this image automated large-scale dataset. historical | In this paper we perform automated analysis on a large-scale historical image dataset. | 15,843 |
streaming a framework to selection. propose covariance perform We | We propose a framework to perform streaming covariance selection. | 15,844 |
the learnt in regularization an be online efficiently This parameter allows manner. for to | This allows for the regularization parameter to be efficiently learnt in an online manner. | 15,845 |
assumptions, non-stochastic Under in mild are results to able convergence a setting. obtain we | Under mild assumptions, we are able to obtain convergence results in a non-stochastic setting. | 15,846 |
on work based Random a model In Field. Conditional Gaussian this new we present | In this work we present a new model based on Gaussian Conditional Random Field. | 15,847 |
CK+ test on work two and We datasets, facial RU-FACS. our train and expression | We train and test our work on two facial expression datasets, CK+ and RU-FACS. | 15,848 |
outperform recognition. that the Experimental approach of state art proposed evaluation our shows expression | Experimental evaluation shows that our proposed approach outperform state of the art expression recognition. | 15,849 |
neural of systems. convolutional image networks (CNNs) the segmentation backbone semantic are state-of-art Deep | Deep convolutional neural networks (CNNs) are the backbone of state-of-art semantic image segmentation systems. | 15,850 |
the target This an semantic optimizing system task-specific segmentation quality. end-to-end produces trainable edges in | This produces task-specific edges in an end-to-end trainable system optimizing the target semantic segmentation quality. | 15,851 |
variational the the linearly memory unlike resources in methods. dataset with required scale size, Nevertheless, | Nevertheless, the memory resources required scale linearly with the dataset size, unlike in variational methods. | 15,852 |
instances number This a is the large. of is very when severe limitation | This is a severe limitation when the number of instances is very large. | 15,853 |
areas an involves problem missing of image. the The inpainting reconstructing of | The problem of inpainting involves reconstructing the missing areas of an image. | 15,854 |
removing old damaged as many Inpainting images. such applications, photographs or has reconstructing obfuscations from | Inpainting has many applications, such as reconstructing old damaged photographs or removing obfuscations from images. | 15,855 |
present this inpainting. for we directional algorithm paper In the diffusion | In this paper we present the directional diffusion algorithm for inpainting. | 15,856 |
diffusion by accurately. diffusion directional The algorithm edges regular reconstructing more algorithm on the improves | The directional diffusion algorithm improves on the regular diffusion algorithm by reconstructing edges more accurately. | 15,857 |
techniques. the Understanding ConvNets process internal commonly visualization of done is using | Understanding the internal process of ConvNets is commonly done using visualization techniques. | 15,858 |
vital recognition, annotations semantic or for scene models Semantic object are training for segmentation understanding. | Semantic annotations are vital for training models for object recognition, semantic segmentation or scene understanding. | 15,859 |
developmental children's in of and drawings God(s) cross-cultural other agents. and supernatural We patterns detect | We detect developmental and cross-cultural patterns in children's drawings of God(s) and other supernatural agents. | 15,860 |
of for and experts These investigation. support the hypotheses findings questions further new raise the | These findings support the hypotheses of the experts and raise new questions for further investigation. | 15,861 |
depth We termed instance novel a object templateNet present recognition. deep architecture based for | We present a novel deep architecture termed templateNet for depth based object instance recognition. | 15,862 |
benefits parametrization template from layer. any this The the from additional network without | The network benefits from this without any additional parametrization from the template layer. | 15,863 |
updates the this in to weight efficiently an needed end-to-end derive network train manner. We | We derive the weight updates needed to efficiently train this network in an end-to-end manner. | 15,864 |
using benchmark for based We object datasets. available the two publicly depth recognition templateNet instance | We benchmark the templateNet for depth based object instance recognition using two publicly available datasets. | 15,865 |
looking The and challenges pose distractors. large multiple clutter, present similar datasets of variations | The datasets present multiple challenges of clutter, large pose variations and similar looking distractors. | 15,866 |
of based alpha method minimization approximate the on is inference Black-box (BB-$\alpha$) new a $\alpha$-divergences. | Black-box alpha (BB-$\alpha$) is a new approximate inference method based on the minimization of $\alpha$-divergences. | 15,867 |
it gradient because datasets large to scales implemented be can using BB-$\alpha$ stochastic descent. | BB-$\alpha$ scales to large datasets because it can be implemented using stochastic gradient descent. | 15,868 |
easily gradients differentiation. obtained can be automatic These using | These gradients can be easily obtained using automatic differentiation. | 15,869 |
approaches, recent video the three Compared representation makes contributions. this inference paper following to | Compared to recent video representation inference approaches, this paper makes the following three contributions. | 15,870 |
operations attaining while Second, lessened non-linearity. are significantly computation more | Second, computation operations are significantly lessened while attaining more non-linearity. | 15,871 |
apply information new to method where temporal video the role. a We plays captioning crucial | We apply the new method to video captioning where temporal information plays a crucial role. | 15,872 |
benchmarks. outperforms our that method on the captioning video Experiments demonstrate state-of-the-art | Experiments demonstrate that our method outperforms the state-of-the-art on video captioning benchmarks. | 15,873 |
neural predictions functions. most provides fastest while the networks accurate metamodel yield the Kriging | Kriging provides the most accurate predictions while neural networks yield the fastest metamodel functions. | 15,874 |
computation All failures. strong metamodels three can detect conveniently | All three metamodels can conveniently detect strong computation failures. | 15,875 |
most find we instability code Kriging tools. provides detection, that useful For the | For code instability detection, we find that Kriging provides the most useful tools. | 15,876 |
time consuming. turns be out quite process the to Thus, | Thus, the process turns out to be quite time consuming. | 15,877 |
above to solution simple approach discussed. novel problem a and Here the is a | Here a novel approach and a simple solution to the above problem is discussed. | 15,878 |
novel based classification propose this In convolutional architecture on ProNet we networks. neural paper, a | In this paper, we propose a novel classification architecture ProNet based on convolutional neural networks. | 15,879 |
We minimize formulated the to method proximal-subgradient use accelerated function. an cost | We use an accelerated proximal-subgradient method to minimize the formulated cost function. | 15,880 |
of its prove analyze and the convergence. the performance We proposed algorithm | We analyze the performance of the proposed algorithm and prove its convergence. | 15,881 |
methods the A novel heterogeneous is fusion approach detection object for proposed. of | A novel approach for the fusion of heterogeneous object detection methods is proposed. | 15,882 |
create spatially to Forest extends (SCRF) Random Spatially Forest Random labeling. Coherent coherent | Spatially Coherent Random Forest (SCRF) extends Random Forest to create spatially coherent labeling. | 15,883 |
in We can SCRF settings that be used believe as other well. | We believe that SCRF can be used in other settings as well. | 15,884 |
which many of in are that remains from there However, far still humans. performance cases | However, there are still many cases in which performance remains far from that of humans. | 15,885 |
allows our network classify even deformations. under to intraclass adoption features samples precisely This | This features adoption allows our network to classify precisely intraclass samples even under deformations. | 15,886 |
should long-term attractive campaigns effectively. To organized be managed these more deposit and overcome problems, | To overcome these problems, attractive long-term deposit campaigns should be organized and managed more effectively. | 15,887 |
applications. in search for vision hashing methods widely-used neighbor Supervised computer nearest are | Supervised hashing methods are widely-used for nearest neighbor search in computer vision applications. | 15,888 |
state-of-the-art batch-learners. hashing Most employ supervised approaches | Most state-of-the-art supervised hashing approaches employ batch-learners. | 15,889 |
large batch-learning datasets. when be confronted inefficient can Unfortunately, training strategies with | Unfortunately, batch-learning strategies can be inefficient when confronted with large training datasets. | 15,890 |
the with online algorithm, approach our an offers size. complexity is dataset linear it Since | Since it is an online algorithm, our approach offers linear complexity with the dataset size. | 15,891 |
to we hash table reduce Thus, a framework also updates. propose | Thus, we also propose a framework to reduce hash table updates. | 15,892 |
networks. of of focus The learning Bayesian these paper this scalable is approximate | The focus of this paper is scalable approximate Bayesian learning of these networks. | 15,893 |
pathways transduction disorders, variety cancer. lead signal can including complex to a Dysregulation of in | Dysregulation in signal transduction pathways can lead to a variety of complex disorders, including cancer. | 15,894 |
Each mutations. of components gain-of-function both loss-of-function under perturbed and model's the was | Each of the model's components was perturbed under both loss-of-function and gain-of-function mutations. | 15,895 |
the of paying both However, and non-dispersal. entails costs dispersal this | However, this entails paying the costs of both dispersal and non-dispersal. | 15,896 |
approximate their to of distributions are methods broadly or posterior Importance moments. used Sampling some | Importance Sampling methods are broadly used to approximate posterior distributions or some of their moments. | 15,897 |
single approach, In proposal weighted a distribution standard samples properly. from are drawn and its | In its standard approach, samples are drawn from a single proposal distribution and weighted properly. | 15,898 |
a formulate ZSR We problem. prediction binary as | We formulate ZSR as a binary prediction problem. | 15,899 |
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