text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
|---|---|---|
methods In approach kernel paper, this data. develop with an to exploiting manifold-valued we | In this paper, we develop an approach to exploiting kernel methods with manifold-valued data. | 12,000 |
be representation. distinguished high-level ambiguity This can by | This ambiguity can be distinguished by high-level representation. | 12,001 |
special of has considered. For case been processes, the Dirichlet streaming inference | For the special case of Dirichlet processes, streaming inference has been considered. | 12,002 |
demonstrate text corpora. the the of efficacy in We documents algorithm on streaming clustering large, | We demonstrate the efficacy of the algorithm on clustering documents in large, streaming text corpora. | 12,003 |
small. might be examples number when Therefore, is of training unreliable the they | Therefore, they might be unreliable when the number of training examples is small. | 12,004 |
is robust overfitting to it small-size training Hence, data. on | Hence, it is robust to overfitting on small-size training data. | 12,005 |
of asymmetric. is majority Unfortunately, models the graphical real-world | Unfortunately, the majority of real-world graphical models is asymmetric. | 12,006 |
for the This relational case representations is when given. evidence even is | This is even the case for relational representations when evidence is given. | 12,007 |
existing Markov such over-symmetric as First, networks. a logic relational all representation require approximations | First, all existing over-symmetric approximations require a relational representation such as Markov logic networks. | 12,008 |
often computed the symmetries significantly, distribution highly the probabilities biased. making change Second, induced the | Second, the induced symmetries often change the distribution significantly, making the computed probabilities highly biased. | 12,009 |
The while leads estimates probability therefore, unbiased. remaining framework, to improved | The framework, therefore, leads to improved probability estimates while remaining unbiased. | 12,010 |
existing the approach Experiments demonstrate MCMC outperforms that algorithms. | Experiments demonstrate that the approach outperforms existing MCMC algorithms. | 12,011 |
Analyzing corporations to Big Data im-prove help efficiency. can their | Analyzing Big Data can help corporations to im-prove their efficiency. | 12,012 |
Semantic Machine-Learning proposea techniques HMC process, scalable We Rule-based reasoning. and also using | We also proposea Semantic HMC process, using scalable Machine-Learning techniques and Rule-based reasoning. | 12,013 |
on We egocentric from task pose of estimation viewpoints. everyday focus hand the | We focus on the task of everyday hand pose estimation from egocentric viewpoints. | 12,014 |
understanding limited. of them remains Nevertheless, our | Nevertheless, our understanding of them remains limited. | 12,015 |
to contribute framework answer invert general this a question we To representations. | To answer this question we contribute a general framework to invert representations. | 12,016 |
In compact learn is binary their embeddings manifolds to on work, intrinsic how this considered. | In this work, how to learn compact binary embeddings on their intrinsic manifolds is considered. | 12,017 |
macromolecules of noisy structural central in is in variability projections biological a Cryo-EM. Classifying problem | Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. | 12,018 |
very easy and Finally, train are to conceptually and use. simple they | Finally, they are conceptually very simple and easy to train and use. | 12,019 |
utility our of Lastly, the on through Internet experiments demonstrate collections. we formulations photo | Lastly, we demonstrate the utility of our formulations through experiments on Internet photo collections. | 12,020 |
everyday objects. pose during interactions estimation we Importantly, with consider | Importantly, we consider pose estimation during everyday interactions with objects. | 12,021 |
performance. work robust depth-based priors Past features for and are pose+viewpoint crucial shows that strong | Past work shows that strong pose+viewpoint priors and depth-based features are crucial for robust performance. | 12,022 |
egocentric workspace. this call volume We an | We call this volume an egocentric workspace. | 12,023 |
appearance property notable A workspace with location. is correlates hand that | A notable property is that hand appearance correlates with workspace location. | 12,024 |
the This simplify performance. and improves architecture greatly | This greatly simplify the architecture and improves performance. | 12,025 |
state-of-the-art method images performance pose hand RGB-D Our recognition egocentric provides from real-time. in | Our method provides state-of-the-art hand pose recognition performance from egocentric RGB-D images in real-time. | 12,026 |
We architecture semantic purely for a introduce segmentation. feed-forward | We introduce a purely feed-forward architecture for semantic segmentation. | 12,027 |
by classified a network. multilayer feedforward are Instead superpixels | Instead superpixels are classified by a feedforward multilayer network. | 12,028 |
distortion a Results for of great type. its effectiveness variety demonstrates | Results demonstrates its effectiveness for a great variety of distortion type. | 12,029 |
uses original other little the benefits about very only this Among image. information measure | Among other benefits this measure uses only very little information about the original image. | 12,030 |
paper, we cost. accuracy time constrained the CNNs this of investigate In under | In this paper, we investigate the accuracy of CNNs under constrained time cost. | 12,031 |
also This the in importance is designs. helpful of for network the factors understanding | This is also helpful for understanding the importance of the factors in network designs. | 12,032 |
state-of-the-art our throughout. we of performance pipeline, stages Analysing show the | Analysing the stages of our pipeline, we show state-of-the-art performance throughout. | 12,033 |
involved cost reduces runtime the in memory in learned turn CNNs. This and deploying the | This in turn reduces the memory and runtime cost involved in deploying the learned CNNs. | 12,034 |
Besides, proposed on the results. more densities significant experiment tissues bring we approach various to | Besides, we experiment the proposed approach on various tissues densities to bring more significant results. | 12,035 |
Base. explored from At challenging Data end, we breast medical some BIRADS this images | At this end, we explored some challenging breast images from BIRADS medical Data Base. | 12,036 |
methods. promising with segmentation mass results the to first Our showed edges regard experimentations | Our first experimentations showed promising results with regard to the edges mass segmentation methods. | 12,037 |
works This this in the discusses first area. paper achieved main | This paper discusses first the main works achieved in this area. | 12,038 |
evaluated concluding paper. our and The results main are before showed | The main results are showed and evaluated before concluding our paper. | 12,039 |
viewpoints. cases, of methods with as large Appearance-based appearances such change changes in fail | Appearance-based methods fail in such cases, as appearances change with large changes of viewpoints. | 12,040 |
computed common different robust efficiently. This be can occlusions viewpoints, under measure to and is | This measure is robust to occlusions common under different viewpoints, and can be computed efficiently. | 12,041 |
is retrieval cameras. stationary held demonstrated challenging Event using from and videos hand | Event retrieval is demonstrated using challenging videos from stationary and hand held cameras. | 12,042 |
in detection image component fundamental and been detection Contour object segmentation has many a systems. | Contour detection has been a fundamental component in many image segmentation and object detection systems. | 12,043 |
related and However, predicting mutually that claim we are recognizing objects two tasks. contours | However, we claim that recognizing objects and predicting contours are two mutually related tasks. | 12,044 |
the This network scales of image different the to is applied four of section input. | This section of the network is applied to four different scales of the image input. | 12,045 |
Why addressed complete? is we here Turing are why, question The | The question addressed here is why, Why are we Turing complete? | 12,046 |
theory we theories. computing fusing build and a problem So by set | So we build a problem theory by fusing set and computing theories. | 12,047 |
is conditions complete. Turing be to The the of last | The last of the conditions is to be Turing complete. | 12,048 |
the most problems. answer would question to be: our to solve Then | Then the answer to our question would be: to solve most problems. | 12,049 |
gradient descriptor, This efficient introduces spatiotemporal called local high histograms a (GBH). boundary paper | This paper introduces a high efficient local spatiotemporal descriptor, called gradient boundary histograms (GBH). | 12,050 |
to GBH spatio-temporal on compute. is descriptor proposed are built gradients, fast which The simple | The proposed GBH descriptor is built on simple spatio-temporal gradients, which are fast to compute. | 12,051 |
the of model tractable inference For marginal likelihood the approximations made. to be must | For tractable inference approximations to the marginal likelihood of the model must be made. | 12,052 |
paper with idea this In compression. a we nested extend this variational | In this paper we extend this idea with a nested variational compression. | 12,053 |
to Thereby, we able characteristic are the objects. properties determine of | Thereby, we are able to determine characteristic properties of the objects. | 12,054 |
a a direct recognition comparison to similar rates. superior algorithm Moreover, shows | Moreover, a direct comparison to a similar algorithm shows superior recognition rates. | 12,055 |
firing and evoked by learn can replay sequences stimuli. Neuronal circuits of patterns sensory | Neuronal circuits can learn and replay firing patterns evoked by sequences of sensory stimuli. | 12,056 |
both a precise order sequences. propose of the timing We for learning event and mechanism | We propose a mechanism for learning both the order and precise timing of event sequences. | 12,057 |
population Learned between another. populations synaptic to time one determine the necessary weights for activate | Learned synaptic weights between populations determine the time necessary for one population to activate another. | 12,058 |
how of inherited The playback stochasticity is timings. determine process dynamics the sequence in learned | The dynamics of the playback process determine how stochasticity is inherited in learned sequence timings. | 12,059 |
cooperation pressure Relatedness affect and selection the and on altruism. synergy | Relatedness and synergy affect the selection pressure on cooperation and altruism. | 12,060 |
complementary ongoing contribute to we but ways. Here, this synthesis two in distinct | Here, we contribute to this ongoing synthesis in two distinct but complementary ways. | 12,061 |
helping. on of This relatedness (or spatial qualitative broadens evolution of the the effects structure) | This broadens the qualitative effects of relatedness (or spatial structure) on the evolution of helping. | 12,062 |
this exploit convolutional to features. propose masking we In via information shape paper, | In this paper, we propose to exploit shape information via masking convolutional features. | 12,063 |
segments The treated (e.g., convolutional as super-pixels) on are proposal feature masks maps. the | The proposal segments (e.g., super-pixels) are treated as masks on the convolutional feature maps. | 12,064 |
take will for emerge? long it to How them | How long will it take for them to emerge? | 12,065 |
our firing-rate self-organization adaptation. questions these on based model address within We | We address these questions within our self-organization model based on firing-rate adaptation. | 12,066 |
significant presents an to occlusion. humans there parsing This paper when is approach | This paper presents an approach to parsing humans when there is significant occlusion. | 12,067 |
a We call parts. connected object flexible subtree composition of each | We call each connected subtree a flexible composition of object parts. | 12,068 |
method a cues. occlusion novel for involves This learning | This involves a novel method for learning occlusion cues. | 12,069 |
we a of inference search During over to models. flexible need mixture different | During inference we need to search over a mixture of different flexible models. | 12,070 |
archaeologists. uninitiated put These off can aspects | These aspects can put off uninitiated archaeologists. | 12,071 |
object spurred research methods. This recent improving in proposal | This spurred recent research in improving object proposal methods. | 12,072 |
stable much Level iso-intensity ones. such more or are under especially the longer curves conditions, | Level or iso-intensity curves are much more stable under such conditions, especially the longer ones. | 12,073 |
stable In corners on on iso-curves we them. this detect portions and long paper, identify | In this paper, we identify stable portions on long iso-curves and detect corners on them. | 12,074 |
the signal. identification-verification It supervisory learned with is | It is learned with the identification-verification supervisory signal. | 12,075 |
Markov the two-parameter overly Kimura complex or model). (the general model) | the Kimura two-parameter model) or overly complex (the general Markov model). | 12,076 |
i.e. eyes salient can recognize on person based identities Human small regions, | Human eyes can recognize person identities based on small salient regions, i.e. | 12,077 |
distinctive is reliable across human in pedestrian matching views. saliency and disjoint camera | human saliency is distinctive and reliable in pedestrian matching across disjoint camera views. | 12,078 |
person methods outperforms approach on both Our state-of-the-art the re-identification datasets. | Our approach outperforms the state-of-the-art person re-identification methods on both datasets. | 12,079 |
of unknown parameters. used compute These estimators are samples to the the Bayesian finally generated | These generated samples are finally used to compute the Bayesian estimators of the unknown parameters. | 12,080 |
We a algorithm Problem. have concrete Traveling for Salesman created the | We have created a concrete algorithm for the Traveling Salesman Problem. | 12,081 |
images We model of regions. generates descriptions their and a that language natural present | We present a model that generates natural language descriptions of images and their regions. | 12,082 |
for importance of of classification. the parts investigate action and the tasks We attribute | We investigate the importance of parts for the tasks of action and attribute classification. | 12,083 |
biomolecules important most Proteins for organisms. the are living | Proteins are the most important biomolecules for living organisms. | 12,084 |
are characterization, for utilized protein classification. identification MTFs and | MTFs are utilized for protein characterization, identification and classification. | 12,085 |
track proposed of origin geometric of the method protein topological slicing The to invariants. is | The method of slicing is proposed to track the geometric origin of protein topological invariants. | 12,086 |
and all-atom coarse-grained representations of MTFs are constructed. Both | Both all-atom and coarse-grained representations of MTFs are constructed. | 12,087 |
end, filtration based correlation developed. a this To is matrix | To this end, a correlation matrix based filtration is developed. | 12,088 |
excellent simulation and between homology prediction An molecular consistence is persistent found. our dynamics | An excellent consistence between our persistent homology prediction and molecular dynamics simulation is found. | 12,089 |
topology-function the This reveals work of proteins. relationship | This work reveals the topology-function relationship of proteins. | 12,090 |
and essentially qualitative limited data (CIA). a such is analysis identification characterization, However, to success | However, such a success is essentially limited to qualitative data characterization, identification and analysis (CIA). | 12,091 |
a we objective-oriented protocol homology general outline methods. this persistent work, to construct In | In this work, we outline a general protocol to construct objective-oriented persistent homology methods. | 12,092 |
EGG generator waveform assembly those neuron based modeled gastric data. using on morphological | EGG waveform generator based on gastric morphological neuron assembly modeled using those data. | 12,093 |
correlation to our based further filtration introduced findings. matrix verify A is | A correlation matrix based filtration is introduced to further verify our findings. | 12,094 |
therapy lumbar as injection images These guidance ultrasound for of act treatment for radiculopathy. | These ultrasound images act as guidance for injection therapy for treatment of lumbar radiculopathy. | 12,095 |
resorting protein the protein one predict without can to As flexibility Hamiltonian. such, interaction | As such, one can predict protein flexibility without resorting to the protein interaction Hamiltonian. | 12,096 |
This algorithm fast work analysis for macromolecules. (fFRI) the a introduces of large FRI flexibility | This work introduces a fast FRI (fFRI) algorithm for the flexibility analysis of large macromolecules. | 12,097 |
The proposed the complexity O(N). further fFRI to reduces computational | The proposed fFRI further reduces the computational complexity to O(N). | 12,098 |
for protein analysis (aFRI) Additionally, the FRI of algorithms anisotropic we propose dynamics. collective | Additionally, we propose anisotropic FRI (aFRI) algorithms for the analysis of protein collective dynamics. | 12,099 |
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