text stringlengths 54 548k | label stringclasses 4
values | id_ stringlengths 32 32 |
|---|---|---|
Previous work on multisensory integration in robotics (e.g., solving audio-visual {{cite:60d630a4fab6cf8cf511da47a064951d0d834778}} or visuo-tactile correspondence {{cite:181e126a19d6a3e05f41f826f0d1710bb293b27f}}) required large-scale data collection on real robot platforms. However there are advantages to a low-cost ... | i | 3063e7bd4e2ce2b50fa78b97674645ca |
We focus on medical image segmentation for validating the efficacy of the proposed VMP framework. We employ three different datasets and compare VMP with two state-of-the-art segmentation networks, a deterministic U-Net and a Bayesian U-Net {{cite:b7c2b058af5f4183ff8cbd6fe8069a2af999087c}}, {{cite:8c1380a35e9151820ca48... | m | 12503d6729fc7ba23c8cac7020ff472f |
In this work, we take a Shannon theoretic perspective at the canonical conditional disclosure of secrets problem to seek capacity characterizations where the secret size is allowed to approach infinity while most cryptography work focuses on the scaling of communication cost with the input sizeOne exception is recent w... | d | 97d05958773e7853d2d1289455b4ca0e |
We also experiment with other state-of-the-art methods, including Vector-NMN {{cite:4213d39d9e1597f179d7864315270573e8d1ae00}}, MDETR {{cite:9702485d8f177933ebf0e601147be072fa9daf00}}, LXMERT {{cite:05edc8fe0729ffcb77abb11a462f6c4e6886c97a}} and MMN {{cite:d4b123cdb6efede6a81f4e7e85027de272b34385}}. We follow the param... | m | 40ddd83a6991e4f7bc9084f6cbf16c3c |
Neural network pruning is a model compression technique aiming to reduce the size of a model's trainable parameters without too much degradation in performance.
Pruning-at-initialization methods, especially those covered in this paper and listed below, work by assigning each trainable parameter, {{formula:25ac8f96-2bc0... | m | 2b352ffb992f77caf6f8928a9cafcb31 |
We propose to use the popular L1 approximation {{cite:213b17a696a4f0bc439d399f2bfbc2c3875d788b}} to discretize
the local and history parts of the Caputo fractional derivative at {{formula:1520dbe3-ebd4-4e80-b598-931a67a301e6}} :
{{formula:69c1ef0c-3a25-484d-8451-bb0f8a96ba02}}
{{formula:ec9b9e84-c214-4b32-8364-8e337ba... | m | 0efcce3a07865dbffbf7fa9fdfab1cbe |
There is a sizable body of work proposing various attack and defense mechanisms for the adversarial setting. Among them, the current unbroken defenses are based on adversarial training (AT) {{cite:500b92e5dd7056065deae6ed246a8052d9bc2aae}}, {{cite:7f57693a5608ec1640303862947ded481c07e7eb}}, {{cite:8702f2389ec4534aafe45... | m | e85d978fd1c340b8a187f97b48f70615 |
The standard way of adjusting mutual information against chance is through random label permutations of one of the clusterings {{cite:5cb81182bbb3ce5b92c1dd8c878dc5566ebf96b1}}. Unfortunately, this adjustment makes the metric computationally expensive. Specifically, the time complexity of the metric is in {{formula:d35... | i | c7d1be6ba51e13fc5d7b6422bbe8e71b |
[{{cite:153d4e2f4b67983740412918473f61bdfb7b65e2}}, {{cite:e1307e83227bf8120f5500d604feaff13252cce4}}]
The following conditions are equivalent:
| r | 3f8a8f958fb7b184c3f14c1b5a7dcb0e |
where {{formula:9240b8b3-9ddc-45e9-bdcd-edc7c38b42eb}} , {{formula:45851c95-366c-4faf-827b-94ebc4da3acf}} , {{formula:1c045fa2-bf86-4aba-88eb-635016151744}} and {{formula:29df7be7-f88c-441c-be24-edead5b65469}} is the corresponding pilot matrix for the user device for the group {{formula:e8331150-93ec-4112-85bd-7f9dea... | d | f1985f6e9a710d347d56966d07212693 |
Although multiple state analysis is not restricted to a specific clustering procedure, we have used in this paper the Ward's hierarchical clustering method {{cite:02cef2ddfbab6821b65f11051c86bdc353f89e82}}. At the starting point of this procedure, each instance is considered as a cluster of its own, then clusters are r... | m | fa77bf4fc3b7f5441a5b0d9c6f3556f1 |
A pressing open question in the field is therefore to obtain reasonably tight bounds for the asymptotic secret key rate of CV QKD with arbitrary modulation schemes, that can be easily computed, without relying on intensive computational methods. Without this, it seems rather hopeless to try to address the next importan... | r | f2ddfacd8868f77a1080b20aded7479f |
There are reasons to believe that the appearance of additional Gaussian in
(REF ) introduced by the functions {{formula:e627fd09-6188-45d9-815c-e781ac2b950b}} will lead to an
improvement in the convergence of the series () obtained in the
framework of the collective variables method {{cite:d5921515462cebbbcc5a9d06dee6... | d | 7106e8caad0ab7ee9b6c6b1583ac2ff5 |
We have proposed a deep learning approach for event-based human pose estimation from a single event-camera. Our method aggregates events into synchronous tensor representations to feed a multi-stage Convolutional Neural Network. Our architecture predicts three orthogonal heatmaps which are triangulated to obtain the fi... | d | 2a9162e196212aee4f00fa6ee558ce4f |
Here we provide more details on the effect of LICE - adding our loss function {{formula:54d0ea0a-8205-4548-aa0c-b37b92c5c277}} to the cross entropy loss in MagNet, DGCN, DiGCN, DiGCN_app, and DiGCN_ib. For a fair
comparison of the methods,
hyperparameters are not tuned; hence the methods may not achieve their optimal ... | r | dbfa45c014025a3d9f89dde92aa9a314 |
Overall framework
The overall framework of our proposed method is shown in Fig.REF where twin Resnet-50 networks are used.
The feature encoder networks with Resnet-50 backbones are trained using the labeled and unlabelled data points using the Sliced Wasserstein Discrepancy(SWD) loss. The latent space of the two netwo... | m | 5294d484b8ec925ff17fa0811c52ba96 |
Dynamics of active colloidal particles such as natural microorganisms like bacteria or algae {{cite:1ce4a2b539d97afb9cd4776da2596cdf1f94b763}}, {{cite:0d134f9172118ddadc0b94a0b9d7bef3ab35542e}}, or synthetic swimmers, active Brownian particles (ABP)
{{cite:f661e36d4dbfb525b996c0ea9651d1e8de184281}}, {{cite:a00b3ae4caeb... | i | 5c7132efed27e2415e05ca0c9fe39676 |
A good news is that modern E-commerce websites contain heterogeneous sources of information, i.e. numerical ratings, textual reviews, images, which can be utilized to help with recommendation.
Through textual reviews, a user explicitly express her affinity towards the item. In both rating prediction and top-N recommend... | i | 53d3947e5a8356215c01db879710db0b |
The {{formula:8519bace-4022-4d9b-8138-11b0f3b2b694}} values obtained with the different reference sources and their average are illustrated in Fig. REF . As already found in {{cite:8f64275bd69ccaff612c5047f4f6d29c2a00c43c}} for the reverberation mapping AGN sample, the reference trends of decaying outbursts yield syst... | m | 651756ac68861e74369a6e5cb6d3576e |
Figure REF A shows the measured invariant mass distribution for selected {{formula:19a4d5b4-2528-4d30-ab4a-d464fe7ae651}} pairs with {{formula:c19559cd-a5fb-42de-bdf3-fa6471771ae8}} MeV from Au{{formula:336480eb-d9f5-4a9d-a4d8-180351d039eb}} Au and U{{formula:cd7160b2-1f72-4931-a92f-147f6ecde317}} U collisions (note,... | r | f7eb1ec0324c367ae2975656d82c66b9 |
On learning the importance and the direction of the word vectors. Our model – by learning how to generate and compose word
vectors – has to learn both the direction of the word embeddings as well as their norm. Considering the norms of the used word vectors as by our averaging over the sentence, we observe an interesti... | r | 25dfbf7e7a1cd791296abb2939385100 |
Long-tailed learning is an area heavily studied in classification settings focusing on class imbalance. We refer readers to Table 2 in {{cite:8984a6d42b7ac9c54eb6008366001036694d00cb}} and the survey paper by {{cite:a2be636726283185230ae3fa8725be71642963de}} for a complete review. Most common approaches to address the ... | i | a6e66bb761ab86619dd43f868c140345 |
Fig. REF shows the minimum on-line training overhead versus {{formula:bc67a089-73d6-4c55-8d92-5d3f7a0405e6}} , with {{formula:3ad83127-a23c-49b7-a931-ca6abbda65ed}} and {{formula:e6537fb1-3aa7-4073-86bc-9d64f17a4471}} . First, it is observed that Scheme 1 outperforms all the other schemes. Second, as {{formula:9569c6... | r | c66b08f0f7fa5230b15c7fa4eb3d515e |
ODIN. ODIN {{cite:2469f981b25719fc153822f0ac3cb692b5b689cf}} got the inspiration from adversarial attack {{cite:7a2ca06dda907d9d598600b0b52a32d1d5026d4e}} and find that including the adversarial perturbed inputs into training improves the final OOD scoring.
Given an input image {{formula:e221f4eb-8a9c-4a6d-8f52-92f6842... | m | 62c6efeb5b3a14c50d3edd0cc73ae096 |
It is well known that, for each {{formula:42cd74c9-fc1d-43ce-93d1-200402e17387}} , we have
{{formula:e130bf59-8d93-4765-a304-2462bb52920a}}
for all functions {{formula:7f9f8989-903d-470b-973a-ce7a180cfa0c}} as in the statement on the lemma, see
{{cite:be0c8eb27a7c3c229867df8a4454de439a2c0dda}}, {{cite:645e136e23e6698... | r | b8cbf2bbebbcc7f2e03f977fc6201f21 |
Clearly, any useful method should be able to cope with inconsistent or noisy data.
A popular probabilistic model of comparison outcomes is the Bradley–Terry (BT) model {{cite:074b715a3f68c3b3bd4dd13bc6b085eae9b94deb}}, which we shortly describe in Section REF .
The BT model posits a notion of distance, or similarity, b... | i | 989f8b4a91ae9c7f6ee741bf2132ecfe |
We point out two remarks. First, the number {{formula:7eee40f0-606a-4570-bcda-5120f7354d7f}} of neighbors we use for our weights-estimation is always {{formula:03122936-8eab-495f-a1d5-785de88c6a83}} . This is because choosing {{formula:ccfb19b6-6a0b-401c-8d33-55ee5bdb93bf}} , where {{formula:b4dbb50a-841f-4add-a4d5-cb... | m | b7d1c2f3276ba8ade4f2feebdb6d6dca |
In the Fig. REF it is seen the {{formula:e1164df6-b4bb-40ce-bf5c-88795f84fecc}} dependence of dynamical mass at fixed coupling, {{formula:b81fa462-95ab-4820-bbb4-e353fc28d85c}} . Near the axis {{formula:9b48717b-fdbf-474c-9465-f716d93fd4b3}} , dynamical masses have no distinct {{formula:3d04314c-7a89-4355-8683-33477f... | r | e0ab637d9514cd31bff9c027bf6f9df5 |
Humans continually abstract concept classes from their input sensory data to build semantic descriptions, and then update and expand these concepts as more experiences are accumulated {{cite:d12771320c1417ef9bd81f471b6ca411fc5f7075}}, and use them to express their ideas and communicate with each other {{cite:a3303f8cdb... | i | 2e06e1672ee32d5a28da1b0ceb24eb19 |
On the other hand, the results of {{cite:c5af3a7612cdd1221dbb7eafdffb1829aff52bb1}} (9 galaxies ranging between quiescent and starbursting, with 6 having measured halo temperatures) and {{cite:8116fd9d4b9a0378d4deff0c5bbbc7a04cbd1965}} (10 galaxies, 7 of which are starburst) appear mostly inconsistent with our results.... | d | 6554ae8cf2c886a96ca77de6ade9b36c |
Taking energy consumption minimization into account results in new
effects due to the additional terms in the learning rule. First, mutual
information reaches lower saturation values, representing the trade-off
between the quality of information inference and smaller synaptic
weights, which limit energy consumption. Al... | d | e1ae3d0653a186fbbd1fa1e7ae597368 |
There are several directions of future work on configuration models of random hypergraphs.
Beginning with theory, many classical asymptotic results on dyadic configuration models invite generalization.
These include probabilistic characterization of component sizes; cycles and parallel edges; and the diameter of the co... | d | acb0f16c931d120cde21f35ad2b76cc7 |
The majority of existing DL based JSCC approaches are designed to operate under specific SNR {{cite:b8f83df083fa8d8aea5161fd0bec438137005ba2}}, {{cite:dbdd45e759b0213daf73c37c18abce15ed0f9b70}}, {{cite:cf3328abb00c6aa86ba6835d0f3adafb3eaf3098}}, {{cite:516225037b3baa8a50fe70a4a461617fe0b4d8da}}, {{cite:c00739f898f564d5... | m | 0d8d89cbf5d914841471710b023b5379 |
Quantum computing promises enormous computational powers that can far outperform any classical computational capabilities {{cite:0e462bd9f0b3ea01ad7893b852bd0a9a4fe9aa37}}. In particular, certain problems can be solved much faster compared with classical computing, as demonstrated experimentally by Google for the task ... | i | 6ef68f4dbf9272e3c6b928d2620936fe |
With the understanding that the black hole spacetime appearing in gravitational path integral represents the (maximally mixed) ensemble of black hole microstates, the results of Refs. {{cite:1538d2390d6ba9a578f2dfd594f96651403632e1}}, {{cite:5b4348b2abe6553774e7dd3c1bfe90c55844b5d4}} can be understood in a simple manne... | m | 3b6262a8d0b3e9b4795207d8544ae9ce |
We utilize the mean absolute error as it has been found to lead to less blurry images {{cite:9be09589b254c830ac12573e0da0db020418ee4b}}.
| m | e463b06f15799a91b9ba4ecc6707c228 |
Current methods {{cite:3911d168ef22872c786d4e41541790e86808f0cd}}, {{cite:5a58f63d602d78bc6baacb83128e308dbfcf3e4e}}, {{cite:8928b51defa1fdfa716b9507ee7a9e7b3316ae99}}, identify the outlier source classes by introducing soft class weights. This signifies that there exists possibilities of some degrees of transfer from ... | m | 95d9655a83525ca18dc3725b07e39311 |
The analysis of long time behavior of infinite dimensional dynamical systems including two-dimensional Navier-Stokes equations (2D NSE) is well investigated in {{cite:64515fccc570a6e86d17604413d83e7acd54839c}}. The existence of a global attractor for 2D NSE on some unbounded domains like Poincaré domains is obtained in... | i | def58fcc2af5f02229218a5d62973d2a |
In this paper, we implemented several existing GNN models, and benchmarked on different datasets for link predictions. We not only
reproduced the results in {{cite:585348bfc8162e21de47c05b7f798a0c6db9150e}} and {{cite:2804d72460614de9b5677f4ae848d03ceaf66382}},
also provided a more fair and systematic comparison.
Our e... | d | aac4cf8ce86a49103ffc99c75d046c0d |
Recently, the role of magic in certain many-body systems known as symmetry-protected topological (SPT) phasesWe remark that such phases are also classified by group cohomology {{cite:3055c1cf467d8cd1261f2799cafe996feac14590}}. has been studied {{cite:576f89704569bb2d14076f55406b8c005e7f9eea}}, {{cite:605629756d8916e5db... | d | 718ead3a5262e88323069696089ec3e2 |
On the another hand, in unsupervised detection, detectors are trained with clean images to identify the ae. It is also known as prediction inconsistency models since it depends on the fact that ae might not fool every nn model. That's because the input feature space almost limited and adversary always takes that as an ... | m | 4f983a0dfde082852f9f157e977fe7a2 |
where {{formula:058e5551-1e3b-4b63-9a6d-e482df64cd62}} is the number of iterations.
If {{formula:3299e99f-8f97-476a-8721-43cde139054c}} is the identity matrix and {{formula:769109e4-51f8-4779-94fd-af67bdce9bd0}} , the resulting procedure is called Gradient Descent (GD) which achieves sublinear convergence for general... | i | a1a61d08fcc5b123f3b00e5e16199d42 |
In Mrk 335, the variability of the UV band is not correlated with the X-ray band on the
timescale of days to months {{cite:98e3b3de1405b5dad552b81f405f1dbf4ac0499c}}.
This rejects models that predict a close link between UV and X-rays: For instance,
models where the observed X-rays are upscattered UV photons; or models... | d | 0cae5353a079e29a53e9abe95e82bd89 |
The SCLD approach to calculate the phonon spectrum has the great benefit that it allows us to trace the vibrational entropy change back to its microscopic origins via an eigenvector analysis. This opens up the possibility to use not only configurational but now also vibrational entropy as a design principle. The good m... | d | f576442d55441d3adf8af250fba28dcb |
In our framework, conviction occurs if the decision-maker's posterior belief about the defendant's guilt exceeds an exogenously specified threshold. Law enforcement is single-minded and only wishes to maximize the probability that the defendant is convicted. In order to obtain a conviction, law enforcement may gather e... | i | aabd214e8345a1c8ceb707e2826a4873 |
Agglomerator brings together concepts and building blocks from multiple methods, such as CNNs {{cite:5070ca90b5645a19228dafe124ddbc20baf3631f}}, transformers {{cite:04e3c9eb6fe3a6c31eb530efacdd4cfb9cfa1f17}}, {{cite:a3cded16abbd0917b6740ce5355d79f4bc6fe38b}}, {{cite:3aabe290ace58a33fb94e9b8b74caf82aa214aae}}, neural fi... | m | f02374bc2fbc25b41c2ffafb4b6bace9 |
Our proof builds on the asymptotically exact analysis of AMP algorithms developed in {{cite:6fdf3868df4ea944b7430156e0dd2e9b1c36c322}}, {{cite:c022cc46d26597ceb4ba0e09af5814e46d4a1a56}}, {{cite:5bb09a103d1bdd62a4ee7535e1f7cb955c71b047}}, {{cite:4f2d1dee154903184517d69b294b96bfbdacdbcd}}. However we need to overcome thr... | d | c892250a6c667257177aa3cba40dc619 |
We run a set of experiments on the CUB200 (CUB) {{cite:098fb2e50aca5af99621e64411fae5ad065809ba}}, CAR196 (CAR) {{cite:2173feeca585748d5a3fafcfe8cea86f069564b0}}, Stanford Online Products (SOP) {{cite:fedbcf201541e93825d158c09c3f59eb6a756f11}}, In-shop Cloth (In-shop) {{cite:c0c3f6ec97a7a2c72639f3f7d2435e26250ad628}} a... | r | 587c4fa26d6723d1b2cb14681110c629 |
(1)We prove that the inertial mass of a microscope particle equals it's gravitational mass. This result is an assumption in Einstein's theory of general relativity and is called the principle of equivalence {{cite:dc0685bc1e53f49c526e7fd942170f90a4594c42}}, {{cite:c03a041e73bf3ee325952cb5a79cc4bf79cca231}}, {{cite:3d33... | d | fac8a39bd28c011517f8faf3e2488b2b |
The motivations for this investigation are twofold. The first is the recent breakthrough observation of gravitational waves {{cite:e44b50a2acc82fdbeaff3eca1c025b9826762f32}}, which makes it realistic to seek their measurable signatures. In particular, memory effects {{cite:39f7425d32027a66fc596b161245761eeb7ecc65}}, {{... | i | 4f5865f788b7ea5e7378e85991358b8e |
There is one other point to be made about the loss function. The abstract idea of a loss function was developed by
Wald {{cite:139a8e2c12997b9925a70888f4c81067908e9b6c}} as a formalisation of the notion that when solving a data-driven problem,
one ultimately has some goal in mind, and that can be captured by an outcome... | d | 618dd8bd4de450f41fb6d235e948552c |
{{formula:6978f4ae-04c3-46ac-aa5c-3b3cfd3436fd}} -order oracle complexity bound. This upper bound corresponds to the {{formula:2bd54e86-4a53-4cc3-8f56-dd3bb7c36ec5}} -strongly convex case lower bound from {{cite:3ddd77b30484bc076f3781862e72f7633d6fa336}} and improves (REF ) on a logarithmic factor. The dependence on {{... | m | f4c44f05607e9dfe63877f5e062cb9c3 |
Subgraph-based GNN training.
The key idea of this line of work is to improve the scalability of GNNs by separating the graph into overlapped small batches, then training models with sampled subgraphs {{cite:a7e0a33caa0d8c48a7940523e7e6ff434868108b}}, {{cite:6c36459183c7ff2b829a9d7158979b49ed73deee}}, {{cite:0b0ee5bb0be... | d | b1065e36a5d7d5e8e51403bb2eb9f540 |
For the first TTS scenario, we train a Transformer TTS model on our Korean male dataset using two GTX 1080 Ti GPUs.
Compared to the original paper {{cite:6b46cdf1f5c66b5b266be86ab69571e088cc47d8}}, we reduce the number of layers from six to three due to the lack of training data and adopt character embeddings instead o... | r | 119ced2ee20a8e616335ea5a2a5bc8ca |
To generate robust image representation, AlexNet {{cite:72507a58177009861043e2856be5bf592e5b129c}}, InceptionV3 {{cite:039cf656b45abeb37e26aeb1e0c7a0a1b2b45337}} or ResNet {{cite:43d2da79fff0867a14b424be61a646acfe1cd2c2}} pre-trained on ImageNet {{cite:a744accc699996b310b6f9ba8039d1e321ee3e50}} database are used. Anoth... | m | d3ab55661e6b0f106f9edde4797c69e4 |
We also use the full shape of the BOSS DR12 pre-reconstructed power spectrum measurements {{cite:f164cd15fb63632025beceea91e287ac102d4b31}}. In particular we consider the combination of the monopole and quadrupole of the power spectra of the three different sky-cuts CMASS NGC and CMASS SGC at effective redshift {{formu... | m | 4844d1324a54ea933dba64e39c02c520 |
Theorem 1 ({{cite:aa6cc9e685861f96a6f78f767d44366c0fca9440}}, {{cite:ef268027be16c63b1cba3dd498a1ad0f54f3f728}})
For any graph {{formula:f3c3bded-3cf5-4f66-9cf3-20a00c61496d}} ,
{{formula:d124382b-d6e0-4747-9719-9790a0c2a6a0}}
| r | 0589e7c0899922642f13ef2c90ffd4bb |
The cluster of particles is assumed to be embedded in vacuum, whereas the excitation field is a {{formula:98279a08-23e8-444d-9443-cd88f448b71c}} polarized plane wave whose propagation direction is defined by the incident angles {{formula:f59152b1-03f7-4919-9abe-898bd5c85311}} and {{formula:16d85929-dcc8-45e4-8a87-be7... | d | d2ff105e0b8908f0942c8a1563bd33de |
Ensemble Kalman methods, originated from geophysics {{cite:76e5f49c39ee0af243e7c9d83f9353f8340521a9}}, have achieved significant success in state estimation for complex dynamical systems with noisy observations {{cite:30f87e3638d25c5ed13bfbe899ab0ff2ea56266b}}, {{cite:c4401e7dfa7be0aeb03317995fc807a198f74609}}, {{cite:... | i | ccf3fcaa9cc0e8f9820e0805bc8a85f4 |
Since a long-run average MDP can be formulated as a linear program
(refer to Chapter 8.8 of {{cite:c279eb9d843ec8cb8b73f1872c88e0f75bdf27a5}}), we can also rewrite the
bilevel MDP problem (REF ) as the following mathematical
program
{{formula:9fd9726e-cf5a-431d-b1e0-7b93e6509a79}}
| r | f631a1298eba90937dc6ad53de93ec35 |
TD error can be used to update motivation-dependent Q-function directly or to train neural networks to optimize their policy. Q-function depends on the new set of variables {{formula:e047710d-3a82-410d-a26b-aac76caefa04}} that evolve following their own rules. These variables reflect fluctuations in physiological or p... | r | d512d40f0a23ed21321dde251ad16b92 |
The same Lindblad equation could have been derived starting from a completely different model, namely a fully quantum mechanical model for the electron on a lattice interacting on each lattice site with a bath of macroscopically many degrees of freedom (so that their spectrum is continuous) that are uncorrelated betwee... | d | 377e24b27b552bad931fc398bd064aec |
The binding problem is also an important topic in machine learning
{{cite:95f24b0ff9422c1feec45a1217299b2f72c39712}}. In knowledge graph embedding tasks {{cite:e939f2c450629ba9ba038f9cf44d049640fcf91b}},
Nickel and colleagues showed that HRR yields a better generalization
performance than methods based on nonlinear-pro... | d | 48b2d193a719cfd0b45aed444b60b430 |
The above intuition is presented by Tian, et al. {{cite:0e3b3c7d4378cbeffdf32931da18cd228876e06f}} as a proposition, which is defined and illustrated mathematically using the concept of mutual information. Based on this proposition, they studied how different choices of the augmented views affect the quality of the lea... | m | 2e08faaf61066f62f7b49fba21f245ec |
We provided a necessary and sufficient condition for
{{formula:eb328f4a-a857-4efc-88f0-c3135c6be2e0}} -differential privacy for mechanisms that add
noise from a symmetric and log-concave distribution (Lemma
REF ). This condition is given directly in terms of the
standard distribution function, the needed scale of the d... | d | 1bf7c5e8c3c0b7c5a8091acd162c3162 |
The notion of discrete conformal structures on triangulated surfaces is a discrete analogue of their smooth counterparts, conformal structures on smooth surfaces. One motivation to study discrete conformal structures is to compute the conformal maps between planar regions in applications. Thurston {{cite:88ab4c4ff2f285... | i | 6de7301619731e1ff5e28cbfe4ed28d3 |
Fig. REF depicts snapshots of 50 trajectories evolving under the classical counterpart of the Hamiltonian {{formula:587a651d-f9b8-419c-8033-18a055048bd7}} used to generate Figs. REF - REF above, with {{formula:104658df-2964-43b8-88f4-f61a745b0aa7}} .
Initial conditions were spaced uniformly, with respect to the ang... | r | 87fa3e49af21df2d381ee4c90608809f |
Our goal is to compare performance of two algorithms, one based on a learned representation, developed by {{cite:5e3b64768473760aeb9d9efa17f515dff457aa2c}}, and one based on a hand-crafted representation. To analyse these methods, we use two different tasks: the first is to find the mid-point in space between two locat... | m | fda59d7defa979d0892a7efdbf9f2d36 |
In this section, we investigate the OOD performance for models trained on CIFAR-10, CIFAR-100 {{cite:18b4bcec05924310d1c37b2b502a2c4744f5f946}} with SupCon, SimCLR and baseline CE using ResNet architecture. We present results with SVHN {{cite:f20729eac76b81704b80a223b3fc300f47a3f655}} and CIFAR-100 /CIFAR-10 as OOD dat... | d | 3dfd6689a82e363e5b8cfa5422ddd1b5 |
Although such works achieved significant success, they mainly relied on classical machine learning approaches, which do not incorporate the graph structure of the connectomes; therefore, the local and global topological properties of the connectomes are not leveraged. {{cite:679aae51ef1d5fd780f72f74f571740fd804654c}} i... | i | e34d1a23910380ff14433b4b9a8c71de |
Many real networks have been mapped so far but there are still complex systems whose network structure information is totally missing. For the later cases, a possible scheme is inferring their topological structure, especially directed or causal networks{{cite:dc47a779e34e430d4e5bd7c4f75e3fed6222f0c7}}, {{cite:2ca8c385... | d | 66d0d94a39fc3e59407ccb2aad1994f4 |
determining (nearly) optimal measurement points is beyond the reach of humans for sufficiently complex systems,
it is important to have a diagnosis system provide appropriate measurement suggestions automatically.
To this end, several (efficiently computable) heuristics {{cite:caf837a20cb5b3e66e5bc2916191c19567e35be2}... | i | 89bd73b1712ec030196e34d3a5ec68af |
for some {{formula:3a599634-0409-440f-b2a5-7eb29794a029}} and {{formula:b50ac852-b8ef-4ac9-9b2d-10d7040877e9}} , and a link function {{formula:aca57599-0c77-463d-911a-540e234a9f63}}
that can be chosen from a variety of possibilities, but is most often
the logistic link function, or the cumulative distribution functio... | m | 37d8423025a5167d1f85958a0ce98c18 |
In practice, one can freely select one or multiple condition attributes for primal attribute editing, depending on the targeted editing goals. In general, to achieve accurate and disentangled editing for a primal attribute, selection of condition attribute is closely related to the data distribution of GAN's training s... | d | 27d858636f8b6f5db66615f4b558b46c |
where {{formula:aa2ef26c-934f-4e22-ad78-6496fff10d94}} is the maximum number of vertices in {{formula:c4cde88f-84a9-4208-9882-d2b9a8f61d0d}} , {{formula:e51697d6-1dbf-4f66-a100-5b74f33c9b7f}} , {{formula:f485e39c-d017-4d52-937d-d21ac08a1621}} and {{formula:d44f0a8c-da61-4c2d-92e3-9c2d243c4416}} is the matrix multipl... | r | 94f469fb1a88e7d5c688bb3a3ee5f433 |
The implication of this calculation is that even though particle modes {{formula:2d274208-32ee-4e05-a7b2-362f39d1aa74}} and {{formula:52243357-1664-450c-9fd6-084505934864}} in region {{formula:919baf69-ffaf-4865-aea8-de63eb1465ec}} are initially maximally entangled, the coupling of {{formula:26393c3c-c6ad-4c1b-a18f-... | d | 7ebf12f77a2b315086f29efbcfd348e4 |
We compare the visual quality of the reconstructed 3D surfaces between our approach and the other two camera tracking approaches (TSDF tracking and surfel tracking).
We implement TSDF tracking with two configurations:
(1) `TSDF Low-res' (low resolution) which allocates larger voxels, so that the number of parameters us... | r | b339f544017c8d263de62c3471b0c882 |
In the literature, several modifications of Newton's method that always yield descent directions have been proposed {{cite:c54e42ff148f44f46cf22666ccea4ca655be5508}}, {{cite:0445ca19e58e24a60514cc43c0cae16601ce74d6}}, {{cite:d688627478efc13294808d415cd1593d82416a82}}. The Gauss-Newton {{cite:d688627478efc13294808d415cd... | m | 8e48645ee617e7171840d1432481bb8e |
The telegrapher's equation {{cite:b3f3e1c80d69ff08efa328b1f5c2421711b82a12}}, {{cite:4c9ebce0fb7479fc968347352e693b5f1c0ea21d}}, {{cite:2de5b2ee9ea346439f186d466a14ef7dc9d06b6a}}, {{cite:f7c987d91045d0420f1a488130834a043afc7669}} may be considered as a generalization of the diffusion equation that overcomes the describ... | i | 515d55855b518e939f88b75e58729df2 |
Let us notice that the {{formula:fe0dc627-4c49-4fdf-918d-f4d55175a34b}} family is the same as the one introduced in {{cite:3e2caeb0d6052c44a4672917be4eacfbd2577f98}}. The {{formula:909016cc-9404-49ae-86e8-acba5849dac4}} equations are divided into two subclasses: rhombic and trapezoidal, depending on their discrete sy... | i | 85cedc09bef95050c0b745b00e4a166c |
The obtained penalty factor of around 300 for each additional nucleon is consistent with {{formula:8329ba8e-c45a-43a0-a04c-cc593f938889}} MeV in the equilibrium thermal models. The measured yields for {{formula:6dc0fd12-0f84-46c7-824b-fd1e1663e94e}} He and {{formula:834a67d5-6f48-4368-8426-d71de764f0b8}} nuclei are c... | r | a012299376f997f7000debecee343d24 |
We propose FedEMD, a light-weight Maverick-aware selection method for Federated Learning. As Mavericks are strategically involved when they can contribute the most, the convergence speed increases, meaning that the learning process can terminate faster and more efficiently. Our emulation results show that the proposed ... | i | 77c064dc18f516951abc9b2206e45cba |
Now we propose a novel perspective to conduct robustness analysis in FL.
Succinctly, by aggregating the shards first, we can reduce the
non-i.i.d. updates to i.i.d. when the shard size is reasonably large, given some
assumptions on the non-i.i.d. updates. As the first step, we introduce the
assumption on the non-i.i.d.... | d | 8172fbfdfa5dd8b0e768fd39042a1f8e |
Many efforts to characterise the dynamics of BANs have already been put forward. For
example, some studies {{cite:f7259b316d32d6d9eee3a6c15d68c4693c17ee58}}, {{cite:4419fcf4c997b135731b1009403c1344c580c841}} examine the behaviour of
networks composed of interconnected cycles. The modularity of BANs has been studied
fro... | i | 3bac86a610e54e9b0825ba0562ca0426 |
As for unsourced random access, the AP is interested in the transmitted messages only and not the identity of the devices. In fact, unsourced random access is motivated by practical IoT scenarios, where millions of low-cost devices have their codebook hardwired at the moment of production {{cite:fcd97589f3c5ae9942df79c... | i | 655d5682efa845a5fdda411b422d2b95 |
These challenges present major barriers to widespread adoption of such learning technology.
To overcome these drawbacks, we propose a new approach to language
induction that takes inspiration from human learning.
We aspire to build a new class of induction systems that adhere to
the constraints {{cite:ef9c7fa33e6302d0d... | i | e4105b37d0f95e6941396903f8c90111 |
In the forward process, the network takes a patch of DI as the input. Firstly, the input data go through a normal convolutional layer and a max-pooling (MP) layer, respectively and then the outputs are concatenated. Next, the contact activations go through the decoder with three groups bottleneck layers. The essential ... | m | 4b503ce5b39ce410098913a71e4b35ae |
where {{formula:47992c09-89bd-459e-ad41-c024c76bab3a}} is the associated graded algebra of the universal enveloping algebra {{formula:d4005900-9ac9-4295-8531-1f2e0e3773f2}} of the Lie algebra {{formula:7edd35be-0e7c-4d6d-890e-c18b96269bba}} and {{formula:028ac8c8-40d9-4bc4-8d17-6dca843a1d5e}} is the symmetric algeb... | i | 6b1405f8cf555fb439c25da57442d095 |
There are several theories with two time dimensions. For example, 11-dimensional extended supersymmetry in M-theory is really a 12-dimensional SUSY with an SO(10,2) symmetry.{{cite:5953d4db4a7b90b62af3a8d60ddf34886cea6f09}}, {{cite:3ee8602aa984a0995959e383bd6135a1fb2d3b97}}, {{cite:1ca9c296be68f15790135adcbe2ca3e76b584... | d | 77521358ff270b5a25ad9ad5295fea38 |
To estimate phonon frequencies we employed the “small-displacement” approach {{cite:50201545ff972acdae600d6be2eac3b8521e7221}}, in which the force-constant
matrix of the crystal is calculated in real space by considering the proportionality between the atomic displacements
and forces when the former are sufficiently sm... | m | 55ce4bd139eb051dcd801e0facbcef67 |
Our algorithms universally apply to any single-photon source, regardless of its operating mode. We enable synchronization in post-processing without modifying the quantum source on the hardware side and without synchronization strings. These algorithms can be seamlessly integrated into state-of-the-art quantum communic... | d | 3ee626be6c15c5021f6831867f89ccf3 |
In this work, we have presented a DICE-based offline constrained RL algorithm, COptiDICE.
DICE-family algorithms have been proposed for off-policy evaluation {{cite:c07e209f7eb346bc26cc74e849b59761bd4d1d35}}, {{cite:a50ddc171ea16825b7e6c93b4173a16262ab191f}}, {{cite:4300c889bace7776ce933a2c43cc4063824bacd7}}, {{cite:0a... | d | fb7fbe6e2209f0082780aa84fc10aebc |
In this context, there is a natural need to simulate the transient state dynamics of condensed matter systems under laser excitation, both for understanding the underlying mechanisms of out-of-equilibrium properties and for correlating the microscopic electron dynamics with the macroscopic measurements, observables suc... | i | 7465ca4f92c52523ef151a8901801457 |
Degree Distribution. The degree distribution of a graph is the distribution of the number of edges connecting to a particular vertex. Barabási and Albert initially discovered that the degree distribution of many real world graphs follows a power law distribution such that the number of nodes {{formula:ccff2716-6023-... | r | 52dc19f45b64fa3ef6536eadf783d872 |
Therefore, we first analyze the classical part of the QAOA on the Qiskit quantum simulator {{cite:8fafad2cb9eff7095f38a5eed6da9ec44f983013}}. In particular, we analyze what makes good {{formula:1680fdc0-e7db-4c1d-ba82-2fc07dfd3558}} and {{formula:8b70a68b-cf41-4c4d-a16a-a24619caa381}} . Afterwards, we investigate the ... | r | 63cd1bcd92c9c855b0848e337b1a0af2 |
Conventional ML models, such as SVMs and LDAs, utilized for sEMG-based hand gesture recognition, typically work well when dealing with small datasets. These methods, however, depend on manual extraction of handcrafted (engineered) features, which limits their generalizability as human knowledge is needed to find the be... | i | a6bdfe39c8a6cdc36e496b09d639c90f |
Linearisation is done around the current iterate {{formula:0ce5edc2-eb41-448e-a06f-78c13ba6abd2}} and the next iterate is the solution to the approximate problem {{cite:10891aedc9d2862f1eec38e96f66db8970767dfa}}.
| m | a6574a2c6cc4c74d385cc04c5241d023 |
Since the most physical systems are inherently non-linear in the nature, the non-linear field theories are of interest to different branches of mathematical physics. The main reason to consider the non-linear electrodynamics (NLED) is that the structures of these theories are considerably richer than the Maxwell field,... | i | 32d4e8f01b27150df05a655b7e801e48 |
Bakshy et al. {{cite:ff028fefcd80cbf26f9c0bc29e7afd7c3b38a118}} propose a partisan `alignment score' that indexes websites on a continuous scale from {{formula:d6633b72-0890-4e12-b203-665afdbddaa4}} (liberal) to 1 (conservative) based on the relative frequency with which webpages of these websites are shared on Faceb... | r | 71629883dc72809598c9a3273d54dd4f |
Modeling Long-term Dependencies. Sst {{cite:7df476d2533e786936263c8c9a344312405851eb}} and SS-TAD {{cite:55ecc75624ffb2801d206a06dfdc8f872ccc2e5e}} which are RNN-based methods achieve relatively lower results as they can not generate flexible proposals. PGCN {{cite:241fa106ef3c03436f53631caac3ee4ed0e990eb}}, G-TAD {{ci... | m | b567d1acb8c8959854b43ef7cdb5e8c7 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.