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To further demonstrate this advantage of ALSO, we turn to Powell's method {{cite:9e3e304242b2d114815747efeb1c266dfcb65d68}} to optimize the parameters. We carry out 8-qubit state preparation as well as quantum autoencoder optimizations and the results are presented in Table REF . In the infidelity (cost) columns, each ... | m | ae8d26ae4ad514d45d52b52e9443b912 |
with {{formula:5225eac0-c0f7-4197-aba7-24f7816b92bb}} GeV {{cite:dc8f8ba30f6329bef5563f14b257b2729a13aa2a}}. In consideration of the {{formula:191e1034-576b-4629-b5eb-ad466d94fc2e}}
in {{cite:f684b1b24c22aec6ca7aa6646a843e04f655f875}} for the decay {{formula:c19e7924-0be7-4a99-b9bf-005a49ae2984}} , one could expect a... | r | 75e2154331316ce96519b8a7861bfd26 |
We propose DF-GT to learn the fusion of multi-rater segmentation labels in favor of the disease diagnosis. We compare DF-GT with SOTA multi-rater fusion strategies to verify that DF-GT contains more discriminative diagnosis features than the others. Specifically, we validate the diagnosis performance of the fused segme... | m | 426cf9fcf6286aac39d0983aa9d5ac45 |
We compare DeepTIMe to the following baselines for the multivariate setting, N-HiTS {{cite:44211f525f14839e7efdee4352d0445482a2330b}}, ETSformer {{cite:22660f0a9329caf257433ac18a0b48680e7f6d03}}, Fedformer {{cite:43ccf16acbaf6c6502edb90e15e518707ba8ffc6}} (we report the best score for each setting from the two variants... | r | 6b12bff2ce6d564e41d0bef528b21b38 |
The equation (REF ) was derived by Hunter and Saxton as an asymptotic model of liquid crystals {{cite:20db57b813ed62c9d48d95d78522c5964758c1ee}}, {{cite:d67b534c6bc77d66d2ed23508621bce5ed361b2b}}. The {{formula:913ebb1c-d204-43b9-8003-0102725590ff}} equation is completely integrable {{cite:d67b534c6bc77d66d2ed2350862... | i | f69b068f6d76b15a72d8cd9c1b65ca3c |
It is interesting to notice that, for almost each pruning target, the estimated operations count of the models pruned using the method of Liu {{cite:444fc568d0ffa491c21758c68436044b7acd59ae}} is greater than the one of those pruned using SWD. It could seem counter-productive, it is actually a good sign. Indeed, those ... | d | 6b62268feff6c0bffe5fa55bffc54e26 |
We propose a special hierarchical architecture of a WGAN that jointly generates
magnitude of multiple resolutions of the same SAR image. This idea of jointly
modeling multiple resolutions was inspired from the Progressive GAN by Karras et
al. {{cite:cce798c21f29d6ee4c6aa2a6808a273ade7533e2}} though their motivations we... | m | cf4b4c4ef966dc1a74bef6113b030756 |
Here, {{formula:2b4a340f-396b-4362-8616-e3b00a4b3a55}} is the observational uncertainty from Tables 7 and 8 of this paper,
and Table 1 of {{cite:73a99390004dbd5f42f2e01c6bdabc5c30fbc502}}, {{formula:3f07f837-7143-4346-ad9e-59a82b683412}} is the uncertainty associated with the model itself,
and {{formula:05fd53b6-f97e... | r | 884241f63d42bf51a33e074800b5d1fc |
Finally, our results and the basic ideas underlying our new scalings can be viewed in connection with in-situ measurements of solar-wind turbulence.
For instance, a (rapid) scale-dependent alignment between {{formula:6db63724-77ca-402e-857b-bde09c2482ed}} and {{formula:5c7eb5b9-e152-42f6-b6ef-8e2b358bbbb1}} fluctuati... | d | 3bed29d645900c24cd76748cde52f5a2 |
Following the semi-supervised learning setting in {{cite:55535cfee3a6a31f2fd720c3c1783e4575b60556}}, we fine-tune our model pretrained by 400 epochs with {{formula:4c7ad908-9183-4e03-a238-8e287703d805}} and {{formula:ca928d10-797a-4841-a0a0-d0a4c7db357c}} of the data split. The results are shown in Table REF . Our me... | r | 70542d52f0caac755572098ce4cd6c1e |
For example, the DP-SGD analysis assumes that
the intermediate computations used
to train a model are published to the adversary,
when in most practical settings only the
final, fully-trained model is revealed.
This is done not because it is desirable—but because there are limited (known) ways to
improve the analysis b... | i | 18be885226e6317c883cf07518368eea |
Partial least squares can be used in many well-known machine learning models, such as kernel regression ({{cite:78230565919286fc7ba8953eabd28c8f88d5417b}}, {{cite:0771fdee6bbe692f246f3ec05fc561de38e585ca}}), Gaussian processes ({{cite:88350ca5d7512b461415880816cbd22a1288efe2}}), tree models. {{cite:809531acd7a3c6d52b60... | d | e3013342c88805f18bbb66c7b51b7b1b |
As shown in Table REF , HumanDiffusion achieves satisfactory scores in the three indicators.
HumanDiffusion outperforms Pix2Pix{{cite:c8a149cf18e95e758c32dc72d383d11e8b13a165}}, SPADE{{cite:ccafb0ab9dcdc3b43548647b25dffc6daf3f6596}} and LatentDiffusion (LDM){{cite:eca9f6243f12dfb44350eb849508ac4dcf34de42}}, and exceed... | r | e84729d4177cece15edd6416379ea9d4 |
Our method is developed to model specific classes of complex molecules (e.g., classes of different monomers or polymers) and is expected to deal with most practical scenarios with only a few dozen samples for training.
However, as mentioned above, monomer data itself is different from the molecules used in related work... | r | 6cbb66aa85b0e991959c2220986c956d |
The offline optimization and evaluation have been studied intensively in the past few years, as deploying a sub-optimal policy for real-time experiments can be costly and even risky {{cite:b4f41b9f5aa1c9ea6a248fd9126478e8ba2d0c97}}, {{cite:7bc2bf2ec893389b25fe9951c5c8f2c7ee164fd6}}, {{cite:7db84a06994235e50a6995cade2ea... | i | 111819dd2a04d064a2aba7ce30986c32 |
Essentially, a GAN with a multi-branch discriminator can be considered a special variant of a GAN with multiple discriminators. Many studies have shown that multiple discriminators can enhance the performance of various GANs {{cite:452896d7bc56a7ff48c10494bcd0adfb8dd1bf96}}, {{cite:922803c2b3a1a9356349ab401c94d9e4fe09a... | d | 389a4f08df79e609b125307dd6e8bbce |
Furthermore, the essential difference between the two schemes for generating PB can be readily understood by comparing the energy spectrum of the system. For the single four-level atom-cavity-EIT in Refs. {{cite:69f8c987c6fb5ce171104ac78ba5d96f9b7e6cb0}}, {{cite:d6430accb4b15c5128a4b7e42262f88ef9dc2f49}}, {{cite:6722a1... | r | 3e3e4f0a8903228aebf2ccad88133af0 |
The heat capacity per one lattice site is defined as ({{cite:7ced4ec13dbf15133abc541816fd4e5bb820b7a0}}):
{{formula:94a23f75-1736-4fbe-a7fc-fd43bcd6a4f5}}
| r | 4e86e6b3419b941d0b2b3da28f85320f |
Appendix
The appendix includes the proofs of the lemmas, corollaries and theorems in the main body.
Proofs
Useful lemmas and results
The following result is in Corollary 4.2.13 in {{cite:d128fddd4b4af8a9cf17df77536ffdc61a17ac16}}.
[Covering numbers of the Euclidean ball]
For any {{formula:1ab04304-c7e9-426c-a56c-91... | d | c90e831823ed95bce78e2dd052cc0b34 |
Many of the major advances in artificial intelligence in the last decade have embraced the use of data that does not follow hard rules {{cite:4659dbad9ec0410b80d6b4c92bc9490934fcb094}}, {{cite:0fccfeb1c9480d6dfa8b2cc0be579b60677f9fb5}}, {{cite:71ae33e3d3b4afce454d44d8c4bebe5d10af2d68}}, {{cite:a2983424d35e5f69804af5327... | i | 3b808fb4313a745e14aab1f156dcb441 |
{{formula:c3dd87cc-0d40-4d92-9461-d14f700a91ca}} USLAM {{cite:707104ef63f77819bdd1f834d008dca8086209f3}} is an indirect monocular method that
combines events, frames and IMU measurements. Its front-end converts events
into frames by motion compensation using the IMU's gyroscope and the median
scene depth. Then FAST co... | m | 4275469a0873093a8ffbedd16520e135 |
Third, when combined with parameter averaging, Federated Distillation methods achieve better performance than purely parameter averaging based techniques. Both the authors in {{cite:3c64260fb344ad4bc9ae87194f9082dce784d736}} and {{cite:2d02a0d67e5cbd35e10b067e3ad66ae587d36f7d}} propose FL protocols, which are based on ... | d | 1da5381a395a58751530791a8955ecc0 |
As shown in Fig. REF , two area (10 bus) system consists of two synchronous generators in each of the two areas with a weak tie line connecting them {{cite:30ec7c727ba9d3de1c310f1669a900f04f62688f}}. Here {{formula:a7877f1f-7218-4c53-af36-d22f4d5dbca6}} is considered as the slack bus. The system is simulated in a MATL... | r | ff9103a6329e4d7610256d401ef413d7 |
The modest improvements facilitated by the weighting scheme proved to be surprisingly consistent across different estimations of word probability derived from extremely dissimilar corpora. Optimal performances using each corpus varied within 1% (cf. also Figure REF ). Other than hoped for, there was no marked improveme... | r | fb71422500144f510e541a2703d61f00 |
CAM {{cite:6597519704128b610e216ed3cf4be8dd95c969a3}} produces a heatmap by taking a weighted average of the channels at the last convolutional layer of a CNN where the channel weights are the weights of the fully-connected layer that connects the global averaged pooling (GAP) value of each channel to the network class... | m | d27d0393dbc0626cd77c2e61b3d3d731 |
Inspired by the widespread success Koopman operator theory has found in a number of applied fields, and its recent application to problems in machine learning, we extended Koopman tools to the problem of deep neural network pruning {{cite:bcd2987b050c17f13386bf92c11103401d11ba8c}}, {{cite:c6fa0304db39f1951066533496e03c... | d | 55526e5f501b8f2bfabb2865b93722dc |
Surface-response functions. In the PCA, the induced charge is strictly a (singular) surface charge, i.e., {{formula:e796817d-d035-413c-893d-6bb9f5fe6d43}} {{cite:5c417c8a6088c697c401c7f50197605696054f7a}}, {{cite:e422b640e8ee672049532b97a1fffcdc789ba7fe}}, {{cite:d4fb7280953debc6c2aac5e8f0f28eed2213e730}}, while in re... | r | fa922a3d2f9a8ab7078137a8a3ced5ac |
As a concluding remark, we would like to present several interesting future directions. The first question to ask is about high-energy behavior of string scattering in de Sitter space. Recall that in flat space and AdS, string scattering has a mild high-energy behavior due to existence of infinitely many higher-spin st... | d | ac64c7eb62a57e452a385d3a995d9f9e |
An increasing number of researchers have studied metaphor from different perspectives in fields like linguistics {{cite:aa22bdabf3cb1f5d8b6c0e6f8803e3a914ac5c19}}, {{cite:4e40746d3431b62ec0257257990daa8379291211}}, {{cite:9c4f0226cdec8deeff9bceae051a724a5d7a1983}}, {{cite:55ba4c77acd465fa2a6aca77e0637cb19f971f98}}, psy... | i | 1fdedc6cfce7089b0a8196f2c183a72f |
Fig.REF illustrates the proposed framework in predicting depth map and 3D vessel reconstruction. It may be seen that our method is able to generate a depth map similarly to the groundtruth depth map, as demonstrated in Fig.REF (b) and (c). However, it is difficult to demonstrate conclusively the superiority of the pr... | r | 5cb23b29a5f2f1c41d5f85f0528ae2bf |
Similarly, MALA is not the only way of doing the sampling. We choose it due to several factors, such as its efficiency in high dimensional spaces, theoretical guarantees on asymptotic convergence to the true posterior, not requiring normalized target distributions etc. The target distribution {{formula:3fde8c76-38bf-41... | d | 1f3aa1331768e309542d837bf94df317 |
In Fig. REF , we finally plot all of data included in Table REF .
The masses are given in terms of the Sommer scale {{formula:d96cc8c6-033a-4262-b4b5-fa635107908f}} along the left vertical axis, while the right vertical
axis is converted to physical units by {{formula:f2751a14-eb0a-4690-8264-cdb19268ee70}} fm The quo... | r | 2201aff36aad91a312838ef14d3364bd |
Our study has limitations as well. As mentioned above, the utilized dataset is still of small scale and, as a result, the proposed algorithms were implemented using repeated cross-validations, extensive regularization and largely frozen pretrained backbones, in order to avoid overfitting and false within-subject correl... | d | 32c70fbc8d847d9381cc181ed636218f |
Although the PESCC offers a factor of 3.5 in spectral bandwidth improvement compared to the SCC, it still does not encompass an entire broadband photometric band.
Therefore, further improvements are desirable as a broader bandwidth will improve the S/N .
To increase the bandwidth of the SCC the multi-reference SCC (MRS... | d | b3e56c4d5b4ed67dfa666187d56846cb |
The above arguments are valid when we only consider the adiabatic
perturbations. It is feasible since the perturbations generated in
single scalar field inflation model are always highly adiabatic and
the curvature perturbation {{formula:b73c8765-be2e-46ec-a053-7d6fa5434bd9}} is conserved on large scale.
However, this... | i | a31a162e0a2a062fe352f1087738d896 |
We conducted extensive experiments to verify the effectiveness of our proposed methods. The experimental results showed that our method significantly improved the quality of generated CAMs. We refined the generated CAMs with IRNet {{cite:edcfbc3fc4584ee78f0f07a627cab0331d7cacfb}} and trained a DeepLabV2 segmentation ne... | i | bac8bd9724abfde52c8c609c34840639 |
The {{formula:9d634f83-d19a-4e9b-8b92-d66b911f8826}} integral is found in tables{{cite:d5b6d606a612e4a4f6640a9d0e3458604a6b8113}} to be
{{formula:7d1e9779-f6f5-4d27-8c20-efeb3f82af94}}
| m | 20e518e668006db1a73589ed7e27ccb6 |
For each target distribution the MATLAB™ program follow a similar setup {{cite:b2757b55d0ffd06c034f023ef146ba392038a6a4}}. First, we set the parameters such as grid size ({{formula:b061d700-eabe-4020-b4f6-08c35493ae00}} ), number of trials ({{formula:aee12fc5-9a04-4563-b872-3d4953799911}} ), number of loops/simulations... | m | c09bb5e8a125c2c6f716a3b62133c010 |
This remarkable result can be proven independently of any specific parameters of the Hamiltonian and applied driving field. Consider {{formula:df533102-ddc9-40c1-8cf0-6a8fd7b7f38d}} and an arbitrary unbalanced Hubbard lattice. Provided both {{formula:ec800f02-15d4-4178-b065-de459d45d04f}} and {{formula:c2e9f491-26a4-... | r | f3f7b602ff7a0007316643eb7cc12747 |
In the present work, we have also provided a first systematic cartography of the special point location on the {{formula:faba3a47-b0d0-4f5d-a848-e56d158fd15d}} diagram using just two physical parameters, the squared sound speed {{formula:7fe4ac1e-c286-48ad-a54b-a3e0cd873038}} and the quasiparticle pressure at the fid... | d | 50830e5066a80ae119c7415f2ed61362 |
Given an arbitrary square matrix {{formula:4663f658-55f6-49bc-aac4-eb2b0fcbbf0e}} , its exponential is defined as {{cite:8d8cdab4d17cb6c0a1822884a518d02dcd6e9d5c}}, {{cite:970f6fb2b0f156e5a00508a702835cd7134d8af5}}
{{formula:f62db8cf-b8b6-427b-8e12-7855db12690a}}
| m | be3f1ba04b2ec2f5d89e081931a21fa8 |
Denote the parameter vector with {{formula:6d70115d-5329-4c23-8873-13c2b550efaf}} and {{formula:0a7d2fb1-7c6e-4efe-a2dc-d05e4bd1711f}} , where {{formula:bfa85edf-7bc1-4f7b-84aa-353d88ecdff7}} is the normalization matrix which includes the different convergence rates for the model intercept vis-a-vis the slope coeffic... | m | ccf585f342fe35663d5643fab501385e |
PSNR measures the image quality by calculating the global size of the pixel error
between the image to be evaluated and the reference image. The larger the PSNR value,
the less distortion between the image to be evaluated and the reference image, and
the image quality is better. SSIM is a commonly used image quality ev... | m | 5e5a94ff5aca4b16312809e252538e1c |
In {{cite:ea4fd7f446ee51f123bd33bcc74c89575671abc6}}, Montanaro showed that using a quantum computer, the number of samples used in Monte Carlo can be reduced quadratically.
| m | 0ffa6ba5d39f956cc6490af7c0d3a833 |
Evaluation Metrics: Classically, MOT systems are evaluated by the CLEAR MOT metrics {{cite:1cfd782577dd681a346cf75bbb34d38a7b47a65d}}. As pointed out by {{cite:545513fb95c0ecbf786173e9eec7c863a800166e}} and later by {{cite:9d79656bb0fb52824a6225fd5a04bc8f868ad69a}}, there is a linear relation between MOTA and object de... | r | 80233afa5f43a15eb08971a4d35ff252 |
Le Roux et al. {{cite:842431a6e85dd12a92e9c7c614195e371e52a6d1}} proposed a randomized variant of the Iag method, called stochastic average gradient (Sag), where the component functions are sampled uniformly at random. The iteration complexity of the Sag method, in expectation, is {{formula:6074647b-c426-4e0e-b4f0-c029... | m | 4b17bc8f960e3d03457df4789b53094d |
Implementation details. Core-set, multi {{formula:692b94c2-0f1b-421b-af1b-65eafe116ab3}} -means, and {{formula:14face71-0bfc-4cf6-896c-c057cc942100}} -means use feature outputs of ResNet-18 that is pre-trained on unlabeled ImageNet using CompRess SSL method {{cite:583a0ea4a67b37e2d91cc019b82b7dd4d1dc0801}} for 130 epoc... | r | 156381d85fa2fbac503912906f9304d0 |
The characteristic equation {{cite:8122be28c6a1ce61141fb1be5f88c9dc363c2ea3}} of the difference Eq. (REF ) is
{{formula:aee0eac2-b900-4cfc-9606-2cdb35e58a69}}
| m | 1b723f89c9202d55069176b593d892d6 |
The various distinctions revealed within {{formula:3dafc3f3-ca1c-4534-9f4f-a07ea7ce85fb}} are also reflected in the
various categories of sets that can be defined within {{formula:f7511957-cc06-47be-a6cf-70722d7220a6}} .
Besides the standard category {{formula:11f7ceae-0044-4c57-8963-033f152603c2}} of sets {{formula:... | i | 998e7b01017af19bd73aeceda8fee689 |
We compared our approach with several existing KBQA methods. {{cite:86238d23196bbdb81833477ea21b33b713ddf021}} performs query building by existing templates. {{cite:1910d86dadf3032c0a2b3fe46d506e0b4daa61a1}}, {{cite:a871c93ae3b717c9d01e8a39cfdd6fad4825d6b7}}, {{cite:e1c19b0f4846cb3f21c7beafe5d49b7f4bbf5f44}} construct ... | r | 42a56ecc049158dbbb3d1926901318c1 |
In the panorama auto-painting scenario we consider a set of photos {{formula:c9af4109-6d7b-42fa-908f-6b7bd5cc90fc}} taken
from the same location by rotating the camera around its center of projection.
We compute a set of homographies {{formula:af8a80ef-547e-40bb-9ad5-f1e7ecae9aa2}} between photos in {{formula:394668c... | r | 97dc49e416b86ab28e524d7b8cb58681 |
where the minimization goes over all possible ensemble realizations
{{formula:b6f43ccd-0811-45b7-89c4-3e3596c940c4}} , {{formula:7ae93ed4-491f-4dd7-86a8-b788167af3ff}} and
{{formula:2def4d6d-837b-410f-a883-eca505eb56b2}} . For two-qubit states {{formula:f4435b89-87bc-4110-9330-5ff1aa0d9c1b}} can be calculated directl... | i | 8eb8874c789df89583b606a80f941dfc |
Moreover, regarding the influence of star–planet interactions on stellar rotation, with ESPEM we recover the results from previous studies {{cite:707b753e1b5c97bc784a924a47e9835d3205e24e}}, {{cite:ae4244169ae896785053b7df55ef3b5203c42abf}}, {{cite:b93af09a0616bf5405f1c6ceb43bcf69318ed4b7}}, {{cite:8c55caa35952e7c4c956c... | d | d8ade00e349c54b78e7f3f556e135432 |
See Appendix REF .
In terms of the linear inequalities in Lemma REF , the optimzaition error {{formula:0f5a8234-a36a-4383-99a3-263dde21e914}} , the consensus error {{formula:eb5adb7d-87da-4ea8-9b0d-a8b7e4c3823f}} and the compression error {{formula:b9fcc6fa-02a8-49ff-84c3-b568c7633ce1}} all converge exponentially t... | r | 1e2d886c25a869ea18b43778abc736d5 |
To verify the effectiveness of the our work, we compare it respectively with several UDA and USFDA SOTAs. The UDA methods include Deep Adaptation Network (DAN) {{cite:7d3f36d44cabcaac367b29fc6c440301ec3ccc9a}}, Domain Adversarial Neural Networks (DANN) {{cite:408b698261eb8613bed33e7c7895f61449f02de1}} Conditional Adver... | m | 2a2826983ca8dcc9dcf2b7ed1c9982d6 |
We presented a proof of concept that, through human-in-the-loop learning, we can train models to communicate relevant information to users under network bandwidth constraints, without prior knowledge of the users' desired tasks.
Our experiments show that, for a variety of tasks with different kinds of images, pragmatic... | d | 847d63c79a334037a19ef27f242977d3 |
We study the evolution of cooperation by quantifying the chance that a single mutant type, introduced at a random node, will eventually spread and overtake the entire population.
We assume that the population structure for strategy dispersal is strongly connected, meaning that for any pairs of {{formula:e0c9a9d9-4258-4... | r | c1c7d9cb2fc1320670beb0bedb511cb3 |
We use conventional Machine Learning (ML) algorithms {{cite:430f629391e9fdc3a72137dc8b87d671979cfe4b}} like Support Vector Machines (SVM) {{cite:cd29ed35f0d98def960c009eaa47de121b150f87}}, Logistic Regression (LR) {{cite:6c19cc96405c732b8416b2f0ceaa44247df6887f}}, and Random Forest Decision Trees (RFDT) {{cite:8be56174... | m | 79ec58668a8cefbaa60bce087ea1d439 |
The problem with the {{formula:2e3e9313-d202-4edb-a052-22670d23beaa}} values of {{cite:4ac27be335b499a27f7b298ac0d5571cd9ca5d25}} is not the same as adopting {{formula:18a69a3f-509d-4f87-b6ee-d357b60bfa68}} mag in order to make all {{formula:3e6706fe-1181-487a-9fd2-1b0be22f7355}} values negative. His {{formula:74bfb... | d | 76a99fa6339e9a55a26a71cf1b7f1e24 |
At the heart of the optimisation problems considered by all these
methods is a term depending on the {{formula:f5954ccd-ddba-47de-94f6-9b3a49fc35cf}} norm of the estimated
precision matrix. {{formula:29e455a2-7a66-4187-b0d2-2170a3bd15fd}} -penalisation-based approaches such as
lasso are popular for sparse regression, ... | i | 158b28e34931e56d74e9c7965d8e1bca |
Following {{cite:2fe55c74feca77e08dca46126ab95a0002ec9cc9}}, {{cite:0980cb7d6f45d3ac49012c272c1362a30f2a95fa}}, we construct our constrastive learning framework with four major components: augmentation, GNN encoder, projection head and contrastive loss.
Let {{formula:5353dd75-efca-40f5-b36c-4c43ab3aabf1}} and {{formul... | m | e357a9caea5e83b590af0a32576a3717 |
This paper aims for promote a novel contrastive learning objective {{formula:41eb4d27-2c2f-4027-94e6-d79d000923fe}} that overcomes the limitations of the widely employed {{formula:c3d1065e-344a-4e13-9973-b2cc65eebaaf}} . While in all experiment we performed, our {{formula:40440a3a-a7fb-48f1-8fac-70318121c227}} outper... | r | 0056930e78b0125b633ca77216e0ad3f |
To evaluate the performance of the designed networks, we resort to the indoor scenario `I1' of the DeepMIMO dataset {{cite:4940c2a43a3ea2366a33a2762ca73c7f43d9196f}}, which is widely used in DL applications for massive MIMO systems.
The BS 10 in the `I1' scenario is adopted as the RIS and is set as a UPA with {{formula... | r | 637fa4f059bc250fbee273cb0184b220 |
This section reviews three typical safe reinforcement learning algorithms: CPO {{cite:73bfd1bb384e539053203140b316e8d6e2bd0155}}, PCPO {{cite:192349a363b473e13d8b8d763f12c0baa2ac0b01}} and FOCOPS {{cite:1bc3498f7cf57e0969a800ddefa59897f82106cf}}.
Those algorithms also use new surrogate functions to replace the objectiv... | d | 61f1009673a8e2e58cab075e5b00e7c2 |
We now move on to proposing the methodology used to reconstruct the 3-D statistical picture of the wall-coherent turbulence, from which the geometric estimates for the representative eddy (of the AEM) would be extracted.
There have been several studies in the past {{cite:0b3e0351d56d69b70853cb358d0c5362744ec462}}, {{ci... | m | 4da9fb8af412861212b517f6dbaf53d2 |
Because of the large granularity of filter-wise structured pruning, there is always the risk to prune all filters of a single layer and, then, to break irremediably the network. This is likely the reason why, in Table REF , the method of Liu {{cite:444fc568d0ffa491c21758c68436044b7acd59ae}} makes the network drop at a... | d | e4e1ec863452cfaf0b4d58cdc1220189 |
Theorem 1 Theorem 2.2 (Chapter IV) of {{cite:eafcbfba2ba59548d9dc9fe9dd69b968488cfff4}}
Let {{formula:727730cc-c15b-47b4-8c1b-243b5fd5f45f}} and {{formula:f525efd9-0c83-4801-92e0-d3312852b7fb}} be defined by
{{formula:cb8e23a3-a334-4c2e-a4db-828b4f560222}}
| m | 186ee7766c32e2fac32d95a8d48f8b80 |
Gogna et al. 2017 {{cite:4f9ddf9953f26655667f48615af709970e10a754}} SAE Reconstruction and Analysis of Biomedical Signals - From Andrzejak et al. {{cite:679219f58a4afe9b829b1e90079bfe77e3a88236}}, 10 Participants (5 Healthy and 5 Epileptic Patients)
| d | 2945bf5d61e293701998e60b9b8c3321 |
In this chapter, we considered a model of an adaptive network and its
fluctuations. We introduced a model based on an SIRS epidemic structure
which included transition probabilities between node states as well as link
dynamics. In this model, the link dynamics are a function of the
state variables, and since the state ... | d | 52d9a3edb40663676db6627881093d66 |
Let us further extend our discussion from deterministic to stochastic methods for solving (REF ) when {{formula:4c580c0f-ea6d-435f-a9e9-157f8598b596}} is a finite-sum or an expectation function.
The stochastic approximation (SA) method was initially proposed by Robbins and Monro in 1950s {{cite:408b8d26bff7aad2c4cef04... | m | 6632a0b579be302eaa0a23ae0f24fcd8 |
Optical Flow
Optical flow models the apparent motion of individual pixels on the frame, attracting widespread attention {{cite:999b5a6108170bb340b578c00a606760b3b359f6}}, {{cite:3b1c9e92e2f60385625b30870556b2dd120e2c35}}.
The optical flow across frames usually reveals the motions of the human subjects, which are obv... | m | bcde4a462958a66ee57be900d054765c |
Table REF analyzes the correlation between human evaluation results of Section and several common automated evaluation metrics for generation. Here, we consider BLEU {{cite:460db2befdf6d5f21a47d2cd9bba53829cc0fdf1}}, BLEURT {{cite:5ff05852166d9752c9b6c27b101759f38d2d8dec}}, BERTScore {{cite:d1fc2e63c034d706aedbc06696... | d | 6a0fd8a4c9bdfc694580e44c785395a2 |
How do micron-sized cloud droplets grow? This question relates to the fundamental mechanisms that determine droplet-size
distributions in atmospheric clouds {{cite:a813466cdf1415a8aaa116e994f8f99d7bfba6b0}}, {{cite:3462744db5d3544623360f11919b14197e0b3433}}, {{cite:aa1f3541021afaaa4bf5a2c4c224792a8b42a6d2}}. In clouds ... | i | 212ccd16169a06eee43189eeaa293cfc |
Tucker decomposition is to decompose a given tensor into the product of a core tensor with smaller dimensions
and a series of factor matrices.
And the best low-rank approximation of Tucker decomposition of a tensor
was discussed and studied in {{cite:fc89dc6f818a7cd68d7826d086f0e7cc43c45659}}, {{cite:375760950053d1248e... | i | b20c539e13f791c84b04ef547a30730e |
At the moment, given our ignorance on possible sources of SGWB, it is then wise to keep non-committal on the
relative speed {{formula:01d28f7e-55cd-4e43-a3af-91c869b7b875}} , and on the SGWB intrinsic properties.
In order to forecast prospects
of detection of Doppler anisotropies, the first step is to investigate the r... | i | ac00c4f4bcb73d8db1946b290b573bc5 |
At low frequencies, the GW spectra behave as {{formula:55843c6c-3304-4711-9608-1cbdf8f11bb6}} , in accordance with the expectations based on causality arguments using that the anisotropic stress of a causal source cannot be correlated at scales above the horizon size at the time of production {{cite:7243f3503e692796430... | d | 944a5ed36eb7698ed16c4e0384558ca9 |
Finally, while RG theory provides a way to predict which combinations of task, optimizer, activation function, and architecture can have winning tickets transferred between them, knowing what is the minimal density of a winning ticket that can be transferred remains an open question. In order to address this, finite si... | d | f52554eab14049545ed7695548b0a205 |
Our approach is achievable for other blockchain networks as well, with the mechanism tuned to the respective consensus methodologies. Ethereum blockchain network is transitioning from PoW to PoS consensus {{cite:6b8fa22835ebe7c5f90a7535f5382fd971a0ba18}}. The transition is supposed to be through enabling the use of Cas... | d | f65c0e8c36f0ab7aa3af8c1029b7b89b |
A phase-folded plot of both the transit and the radial velocities is shown in Fig. REF for the eccentric two-planet model. The radius for TOI-1422 b was calculated with the transformations provided by {{cite:caf51cf6618610828593ae521494f09c1de48dbe}} and, using the stellar radius of Sect. REF , its revised value turns... | r | d7716a5bcd326c61fcce6266eb98448b |
Some of these multiscale methods, such as the heterogeneous multiscale method (HMM) {{cite:ef99aa03304f24a4efe18cdd36cffb6e69d0de08}}, {{cite:d8fbcad47c73deff3b0ac4af98732d7ef5be6268}}, {{cite:4a61f33aeed17eb07f4f762570d17c4cca56d78f}}, are based on ideas from mathematical homogenization {{cite:ba99f8a929c659f09ae70d2d... | m | 1d9649da937f3fe4479112916d2f04ab |
Turbulence and multiphase flows are two of the most challenging topics in fluid mechanics and when combined they pose a formidable challenge, even in the dilute dispersed regime {{cite:ab759730e2964d44c759c89dece07c9dce65a104}}. The focus here is on liquid flows laden with disperse bubbles, which can be particularly ch... | i | 38afc5d44d8920fa05f1aaa0a878c638 |
We also developed a toy model that reproduces the features of
angular momentum evolution. This model has adjustable parameters with
clear physical interpretations. The relation between the appropriate
values of these parameters and the physical variables requires more
detailed and extensive analysis, which is currently... | d | faa1c9f862648d09744e062f56cc6063 |
4) Learning performance compared to SOTA To further evaluate the performance and reproducibility of the results of the proposed Dirichlet policy, we compare it to two alternative RL algorithms: the original SAC {{cite:9034ee49c44d8d88df684e8abede191ec59c7a7b}}, one of the state-of-the art reinforcement learning algorit... | r | 7efd07d37acdb479deaa7715fe0e03b4 |
Table REF shows quantitative results on JAAD and TITAN datasets (results from training stage 2). We compare our method (GPRAR) with other methods in three different observation modes: noisy, pre-processed, and ground truth. In the noisy (raw) mode, the observed data (poses and locations) are the outputs of a pose dete... | r | 1d1be2ec3c8970e62f369a23be01a760 |
Please, note that the results that we are listing in this section do not correspond to our best results, as they are obtained using a random set of initialized weights as opposed to the best solution selected out of multiple runs {{cite:c506f24c1e17db5e985b74bb5774647353dc03d9}}.
| r | ffc2140d7c97d5132005a0f9973b3257 |
The last situation we have considered corresponds to {{formula:4e090881-7206-4c33-bafb-f4a61c0e4d44}} , with transversal splitting on.
This parameter measures the frequency of transversal splitting and is expected to increase with {{formula:90749a9c-e30e-4ee1-a249-391e32a0d5d1}} .
Accordingly, the system can change fro... | d | 11f39f6971269bbdf1a024665b5d2274 |
The proposed filters and Sobel 3x3 {{cite:e9185016b09d38d9d731dbf3f0745b8a5ba36c1e}} used in the Canny algorithm {{cite:bf467bf5f20e5e4570915eaf53fb76ba2ad331f0}}, {{cite:92290d4ec53f5cdc2d8049ce39d30af517600192}}, shown in Figure REF , REF , show good results in maintaining a balance between filtering out edges that w... | r | 291b8edcbdf1482dbf7b0ab5d479b072 |
Even if this paper focused on the simplest toy scalar LQG problem with two controllers, the essential difficulty of decentralized problems — nonconvex optimization over infinite-dimensional space — was still there and we could finesse this difficulty by taking an approximation approach.
We believe the approaches and te... | d | 97655471ed5674d0558b0196e5d5a23e |
Temperature dependence of the amplitude of the oscillations at 210 kOe follows the standard Lifshitz-Kosevich (L-K) expression,{{cite:c6d9032cd55eaf9899df9bd2f557dc57edaa6bce}}, {{cite:e2de2d1a4488e53ded7217881e3b8ef86bbe1b90}} as shown in Fig. REF (g) by the continuous curve.
The value of the effective cyclotron mass ... | r | 678b2143c4a737cc887be9b38e492b64 |
Our results are of particular importance for non-equilibrium phase-separating systems. By combining previous results from the mathematical theory of CRNs {{cite:c264fe6c5c9ccc8d8bb8efa18245e8808c17a38c}}, {{cite:c8c958da8441e4755a4b8039e387c1da4cbd3ea4}} and concepts of non-equilibrium thermodynamics {{cite:398e206c1da... | d | b481a1a813d20f433d7c0307360872de |
Before introducing our method for reducing communications, we begin with a brief discussion of the classical HB method {{cite:f02591d93f238bfa429736463f332c26567a1730}}, a popular iterative optimization algorithm, and focus on its parameter update rule in a distributed system with a server and {{formula:71158e51-8a40-4... | m | 3736825fd1125bb3395c3b1c16203608 |
Throughout this paper, we use the notations and methods well written in {{cite:fd581a912dadd84e34bffd6b7d18d56c7ec90235}},
which we have adapted for the weakly associative case with some modifications.
Further in this section we give some important definitions.
| m | fce93e1cfb382d7a7d82ac953c513569 |
In this unsupervised setting, the standard pretrain-finetune transfer paradigm becomes inapplicable, as there are no labeled images available in the target domain for finetuning.
This requires us to conduct unsupervised adaptation between two different tasks, i.e., train a model on the labeled source domain and adapt i... | i | 8f0c47505a667284cc90a400c6b5d66c |
Then we apply the unsteerability criterion for two-party {{formula:1fadae4c-2db4-474d-8f86-87e101b8c67c}} -mode GSs,
under Gaussian measurements, found by Wiseman et al. in Refs. {{cite:3587a2e0784f75dce8d467f2a57b3d3a5cfa6c1b}}, {{cite:3907765dc94ed907d9b7e66b8a2c587e4116dc89}}.
Accordingly, the matrix inequalities (R... | d | 893f3361e097d92256e52a2dd8270610 |
Before we move on to interpreting our results in a broader context, we must first establish the accuracy of our derived dust parameters.
Previous studies focussing on modified black body fitting of the dust emission in compact galactic dust cores (e.g., {{cite:56b98e92381b0b9f4f2e26ead58799f03fb37cc0}}, {{cite:31b103a8... | m | 2849533611438dc176251560ec9efae3 |
These approaches rely on label information to retrieve cross-modality instances. Yagcioglu et al. {{cite:4755296dac0e58b0150e6b67672dcb77fe1e069f}} used a CNN-based image representation to translate the
given visual query into a distributional semantics based form. Furthermore, selecting intermediate semantic space for... | m | 2d22bf61113ba6e2e98d61facc8f197c |
Despite their success, there still exist two underlying limitations that hinder better exploitation of base-class knowledge, as illustrated in Fig. REF .
First, region-based detection frameworks rely on region proposals to produce final predictions, thus are sensitive to low-quality region proposals. Unfortunately, as ... | i | 087d5a293d406495489750188dd28001 |
As coloring is hard even when {{formula:96cec8f8-7177-4e17-9c6c-49fc9a3b49b3}} is 3 for general graphs {{cite:611672c01074b3e3c13a95f46c8aecbb0991d5b2}}, we can rule out any fixed parameter tractable (FPT) algorithm parameterized by the number of colors for BCP for general graphs. In this paper, we study the complexit... | i | 133c11cccdff18dd0488e63ee9bc8306 |
In the topological method, we generalise the above concepts by introducing the notion of walk-matrix.
For the entries in a walk-matrix, we don't necessarily use trees of self-avoiding walks. We may use other
topological constructions of {{formula:449777b1-080b-4d66-a658-9a3417070a61}} such as path-trees, universal cov... | m | d706b69e97369db582089cb1fc7eb807 |
In this Section, we describe an application of Corollary REF for accuracy of approximation of the impulse response of a single-input, single-output dynamical system {{cite:32d45c53e93d81f67a1047a0716a553f1028fa6a}} based on the Arnoldi type method of order reduction.
| m | 9bd88f091344842067693b528d87ec5a |
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