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However, there are two issues in current few-shot learning studies. First, mostly studies focus primarily on English {{cite:fc64e8cce6371f02bd9631de9f6d6cd8dc4d3f2b}}, {{cite:9cda1e467c17a49964abc06e8a166304dc2fc179}}, {{cite:1ed639a2ea1059412cd5d905803405665942133c}}; it is unclear how few-shot learning will perform i... | i | cbe6cfd1d3212c4f104f620e0d53a10b |
Problem (REF ) is a standard linearly constrained convex problem, and many algorithms can be used to solve it, e.g., the primal-dual method {{cite:ec0095d60a954c489176bddf668e1e6608c15142}}, {{cite:92b786c2c296c38131b992b14f901f97ac1896f2}}, {{cite:84153e2f3d3d27515145aee9c125acd8b851bece}}, {{cite:6db6de63a63b82a783c0... | m | a7c7b8598d80f7b183a0fe8c6b0ba920 |
A Moebius–Kantor complex is a 2-complex with triangle faces whose links are isomorphic to the Moebius–Kantor graph (i.e., the unique cubic symmetric graph with 16 vertices). Every Moebius–Kantor complex can be viewed as a nonpositively curved 2-complex, in which every face is isometric to an equilateral triangle with s... | i | 924c5c8f83276995f444e72e63a8b436 |
These quantities are then combined to generate the final PIs.
In the paper {{cite:7028ee0e7c61fb02c7118b5586aac7697c87f3d0}}, the aggregation is done as follows:
{{formula:940f4ec7-652d-4ba0-8c3b-c1cee825e5db}}
{{formula:26859b8e-6a93-475d-99eb-ed5313d8a9d0}}
| m | 1f1d74e627819b0fe702552785472065 |
We then select the model that is the best fit to the data, out of the above five alternatives. This task is performed using branch length data across different clades on the squamate and angiosperm phylogenies. The best model is chosen based on their Akaike's Information Criterion (AIC) values {{cite:f3d2e796b41b6742de... | m | 0f80fc714e755a3d709c934bb09c1ce6 |
In this paper, we conduct a comprehensive evaluation of canonical deep network architectures and data augmentation strategies. Our architectures consist of (1) a convolutional model, (2) a fully-connected model similar to MLP, (3) a recurrent model, and (4) a transformer. For each model, we evaluate five augmentation s... | i | c82ccb587364b8ddc9a9e93064c6cdfa |
Now we are in position to investigate the heteroskedastic principal component analysis in detail. Suppose one observes i.i.d. copies {{formula:e3ad1637-812a-4bce-a202-9d2a53f7dec5}} of {{formula:a42ac06d-3c9e-4123-bfc1-4f148f6651cc}} from the generalized spiked covariance model (REF ).
Let {{formula:451f5535-fe6f-4e4... | m | ab0509b97c1c9a637db49294661fc94d |
The first one is the classical Riesz-Thorin interpolation of real functions (see {{cite:72ead13f5c28ab802064ebdeda03b112bec34aa5}} for details on the proof).
| r | 371799062d65b712997a7e11b818af3e |
While related, this challenge is subtly different from the well-known divergence issues of off-policy learning with function approximation,
demonstrated by Baird's famous counterexample {{cite:3d374be291b3d75180d3f3da1f389982f12a2bf4}} (see also {{cite:9a36e01b927659fbe2d4be44e895888ff6e9ec6a}}) and conceptualized as t... | d | 47010439fd4e54f862841ca64b815020 |
Sampling and counting are related problems. For many counting problems, approximate counting and approximate uniform sampling have the same computational complexity {{cite:0900eb3824b9431e4c66e370acc8fb4d254beb50}}. Therefore it is natural to consider the problem of counting the solutions to the edge {{formula:3846d4e5... | i | 8d0a7d2c3e6f65018e8b4fbf0175d782 |
We then generate an alignment path through this matrix using fast-DTW {{cite:6ab5a91f4830d3513f40ee83b258fce1d27b7ff0}}, through a readily available DTW implementation in Python https://pypi.org/project/fastdtw/. We test the performance of our model on a subset of the Mazurka dataset {{cite:3bf6d709e71dcfe9e1640094dbd6... | r | dc4f53b1942e74d6438461307263be76 |
For all datasets, we first calculate the set-2-vector embeddings for all baselines and SWE. Then, we apply Locality-Sensitive Hashing (LSH) to the embedded sets and report Precision@k and accuracy (based on majority voting) for all the approaches on the test sets. We use the FAISS library {{cite:d458b6579c1321319a7c3d5... | r | 3f86ab12a227a23db083de4139aaf216 |
We compare our method with the following five methods.
Following the recent studies {{cite:966aebbbda94818990164e705ce1b0b4e88d74f4}}, {{cite:989cf0a0c84a418253cfa5e58293d6a8dca0dc62}}, {{cite:07eaf735dbabbfb9ace94c88b84060af8c349ad8}}, {{cite:4b90ce35433ddc03b578f265b2f711493dcfba3d}}, {{cite:93b17b858784143faa4c207f0... | m | 5fc5681da0e8c54bae28e9e6f0a95195 |
The solution of the weighting method is weakly Pareto-optimal under no additional assumptions. It is Pareto-optimal if the weighting coefficients are positive, {{formula:211faf14-f917-49a4-8f97-b4719f34ddc8}} . The solution of the weighting method is properly Pareto-optimal if all the weighting coefficients are positiv... | m | f7a64cf7354565d8f3554e38569f4c14 |
Literature search: To get a comprehensive overview of how dashboard is evaluated in healthcare, IEEE Scope, ACM Digital Library, Google Scholar, and PubMed were first searched. A combination of the following terms (including terms obtained through affixation) was used to search in titles, abstract and keywords: dashboa... | m | 392b7cd35e158fa13368c7dbace7551d |
Hofmann et al studied the four-partite entanglement in the {{formula:6dd9e6c9-e061-480a-a10c-f68a58abc4b7}} chain by using the genuine multipartite negativity, and found that the entanglement disappears when the distance between any two spins in the four-qubit subsystems is larger than 2 {{cite:7d76799bf7dd3c76301faba... | d | efeff0723871b03e3c9b143c932bc473 |
where we used (REF ). For {{formula:b5fef9d8-390e-4fc3-942e-4ef506bd2bb1}} to be a valid zeroth-order approximation in the Solovay-Kitaev theorem, the following condition should be satisfied {{cite:0a963df768e184cd7126bd5d96bce0c6902d5ab1}}
{{formula:42c34ac8-a6a9-4ede-8a1f-db3e4599c3d6}}
| d | 07b3149aecb9d0ce6ba9dc44e65a19b9 |
which have much smaller uncertainties than the world average {{formula:0b5a7a45-530f-4529-a0c0-c13eeca4727d}}
{{cite:5dd82e735b4a52c06f44f03cca455e22c4d98539}}. A renaissance is expected in the
study of weak decays of singly charmed baryons.
| i | b668b7231b40c8c3175eab3f6c2954ae |
We then state the results from {{cite:243a195b32fcf2edae22773aa1f7f5b31dfbf34c}} under our notations.
Suppose the following conditions hold:
| r | d7e7a6f2d0a85993da1e2b41d72eee16 |
The work of kim2014temporal was seminal in the sense that it is arguably the first one employing prediction-based word embedding models to trace diachronic semantic shifts. Particularly, they used incremental updates (see below) and Continuous Skipgram with negative sampling (SGNS) {{cite:f328dc0b5c92dad6ad7c9f66041e89... | m | 65f309ee4a5b573a8a69fa4e3c536874 |
Despite the recent successes of MARL, learning
effective multi-agent coordination policies for complex multi-agent systems remains challenging. One key challenge is the off-beat actions, i.e., all actions have pre-set execution durationsIn the RL literature {{cite:fbbe8e9d8c9aee2b1bf6b43023aad834cb1d79c0}}, {{cite:dfbd... | i | c8a8736b0fea686412deecc7b784ecd7 |
It is reasonable that emotions have emerged in biological life forms for granting some evolutionary advantage and Darwin already noticed this in 1872 {{cite:146f405bf9df24a07be0e6a75b82c1c31e1c559e}}.
For instance, some emotions are useful for self-diagnosis purposes, e.g., anxiety and disgust, while others may help in... | i | 9cc4a384663715e30c13afef0f35b988 |
The accuracy is usually measured in the following two forms.
The fidelity of two quantum states {{formula:2114cd98-aa68-475a-b0d2-dbedf6e141e6}} is
{{formula:5e97b3ab-3583-409d-b0cc-a0195501bddb}} , then
the “infidelity” is {{formula:7705d4c5-5e00-4119-a054-a33fb6531e7e}} , represented by {{formula:56bf0714-9458-4670-... | r | 699a218b9e77d2edbc2a1eb7912f5637 |
We evaluate our model through qualitative examination of the generated videos (Section REF ), analyzing color change over time (Section REF ), computing the FVD metric (Section REF ), and ablating the key design choices (Section REF ). We compare with StyleGAN-V {{cite:160a238b98130e5c7a135efe51b4b2a6166dc6ed}} on all ... | r | 2b8c9dc4a5a2549183de4d7db206cf67 |
Human Pose Estimation (HPE) is a fundamental problem in computer vision.
HPE aims to obtain the spatial coordinates of human body joints in a person image, with a wide variety of applications such as action recognition {{cite:f3d714a4f4088ef6c7a845ee045053bcb96a43d7}}, person re-identification {{cite:4922c52a98b9533cf6... | i | c83e0c686d607c549376e5910d98aae8 |
where {{formula:2f75c84b-fd7d-44e5-971a-f86b90cc8bdc}} Now, using Lemma 2.9, and the proposition at the page-92 from Marshall et al.,{{cite:eafc60cace0dae6d02e5dac968ae4ba3c1f52f9a}} we can conclude that {{formula:41518654-1544-49b9-b26a-f167eac5f58e}} is Schur-convex in {{formula:d1d55011-450f-4734-b791-2b902af69297... | r | 9462d09ef0f490722222825aa0360d88 |
Occasionally, the need to account for certain truly multi-physics or nonlinear phenomena brings up opportunities to develop our understanding of wave physics in temporally inhomogeneous systems: for instance, in order to realize bench-top analogues of relativistic phenomena early attempts were made to tap into time-mod... | i | e8ed1ada7cbcdf23f8d79bab72f06603 |
where {{formula:82cc31d2-5591-4be7-9ed6-cb9b20ba875b}} is step-size, {{formula:2e24c09c-7b2b-4831-952d-3d53c7388908}} is a stochastic estimator of policy gradient {{formula:c7aa9a5e-2004-49e2-8b7c-87c5243b3690}} .
According to {{cite:f4e8e09ce925717c872507f31d0ed95620b55d3b}}, we present the well-known policy gradie... | m | 89ffb9409539cae3f96db3a7fbbab6cd |
ANN to SNN conversion (ANN2SNN) {{cite:80f11a626980488686eb81e5fc1ea876121ede3a}}, {{cite:4eb8dca24988f5d693f4b894373fa751282654e3}}, {{cite:f16ae7594070f8ac36185223c015005c7e644209}}, {{cite:303a794d0b4d1d4e0cde7e6e1afc8403b149d9f5}}, {{cite:c4de8c27b060cce2d4e95ceb42825fe5418b793a}}, {{cite:d1c9c154dc9a71c8dab07509ae... | m | 997455b6cdf181bf4ace2a004a1a5eeb |
Theorem REF allows us to show that the distance between subspaces spanned by the {{formula:0c1f835d-3d4b-4fcc-a5e1-9fb0645faa97}} leading eigenvectors of {{formula:6f28ca48-66aa-463e-a9dd-f903ca3d55ca}} and {{formula:6ba4ea15-e0f5-4f04-b461-5da6aac36b2f}} is bounded. The well-known Davis-Kahan theorem {{cite:ccb4b9... | r | f285936312f20ddf3650d714ccc186a2 |
According to the same jargon, when the differences {{formula:0e6f7289-a8d8-4d1f-a36b-2708b09c1991}} AIC and {{formula:69891e59-580f-4e08-a4f1-34d2dc63aefb}} BIC are both above 10 one speaks of “very strong evidence” against the unfavored model (the {{formula:4dcc9bd5-5e85-4afe-87ae-3b612c13461e}} CDM, in this case), wh... | d | 5dd7c321cb7a906aa45ab47ac76b3fba |
Using high precision arithmetic and the re-orthogonalization algorithms described in {{cite:1d648730370638a4a68ee438df69f00d103a73fa}}, we computed the Lanczos coefficients associated to operator (REF ) for various instances of XXZ, see Figure REF . Then, following the discussion in Section REF , we plot in Figure REF ... | r | fb8dd289c916e4d49ac5b025a27b5f35 |
The numerical explorations in this paper have opened up interesting questions that can be investigated in future work. These include a better understanding of the onset of oscillatory behavior of the expectation values as functions of the Barbero-Immirzi parameter {{formula:daf7c52c-271f-4d94-ae80-2dcffa14f104}} , whic... | d | 8f5139841342144174009aca3359c9a2 |
This section presents qualitative results on one scene from ADE20k {{cite:32967f56eaf8aa7f6dc2ef78aaf270f63e72eee9}} in order to illustrate the impact that different class orders have on the final predictions and how the foreground-background class-balancing can mitigate some of these problems.
| r | 976a62a19fb695550f8c1ba44bb697de |
A prevalence of (1,1) modes in this star, and in {{formula:a9d23a77-61c1-49ee-a45c-50ca026696bc}} Doradus stars in general, is beginning to emerge. This includes two modes in
HD 135825 {{cite:811d129f1c7e122d39235eb7ca72f9fe88bcf3f8}}, two in {{formula:0983d4bd-a6b7-4c35-90a0-edda93aa5970}} Doradus {{cite:d6fc88b123c... | d | 38eacb5890800e77fc687276f994fc6b |
where {{formula:9bf486e1-b6a8-4fdd-b4d2-950d0687f0b1}} is a fixed entropy term so the temperature term {{formula:1e2f8015-5381-4998-b3b2-207ee543e7ac}} is
generally decreasing such that the degree of exploration is reduced as the training proceeds{{cite:db4dca708f8f6541b100b1e26f14b8be04888435}}.
| m | b0c378b291e8ef265c0182747c819131 |
Feature subsets – We then evaluated different feature subsets to assess which ones had greater impact on the final performance. All the results presented in Table REF used a the small model of two layer, 64-6-3 feed-forward units. The three statistics (arithmetic, geometric and harmonic means) of morphological feature... | r | 86ceeb9ece2526573db34e7fd421d46f |
The present work demonstrates the compatibility between microwave optomechanics and ultra-low temperatures. The next generation of experiments will incorporate a TWPA (Travelling Wave Parametric Amplifier) in order to open the detection bandwidth, potentially down to the phonon relaxation time, while reaching the quant... | d | a3ac2c2113792a7bd362458d59e13c2e |
Next, we focus on the interlayer symmetric exchange interactions and our DFT+DMFT results show that significant antiferromagnetic (AFM) couplings exist in bulk Fe{{formula:f523a286-9688-44ba-af23-7c77365e976e}} GeTe{{formula:29298b5b-8085-45da-9828-7d36613258fb}} , as already discussed in the literature{{cite:77fdb48ad... | d | 241869398add3415d059b92f6eb9d834 |
A technical aspect of the LMBJ potential and its parents BJ {{cite:11346f875933f2dae8346bd6fc2d525d650836b8}} and MBJ {{cite:80564eff690d075da04554da902d88a2f5f92a3f}} as well as AK13 {{cite:9470945b71057fc7181388bacbb5e227c4130e6e}} should be mentioned. As discussed in Refs. {{cite:11346f875933f2dae8346bd6fc2d525d6508... | m | ecc8fa38dc10d11692fa16579a207a15 |
Keypoints Regularization. Ensuring a shared representation and temporal coherence is important, but not sufficient to ensure the encoded keypoints capture meaningful information about motion.
Specifically, the keypoints might collapse to a single point without any relation to the object itself. Therefore, we suggest ... | m | ee410b9e84881e6d0d968c414a0abf1a |
If at {{formula:186fa596-c7d7-462e-9613-de6694a7bd99}} an initial distribution of {{formula:44e8553e-c0b1-4270-95d9-03d9e517dadc}} walkers {{formula:3e63b1aa-1ee2-4619-9d3f-f1e43eb73fc6}}
is generated to be equal to {{formula:b743bec5-a389-4f16-a398-6b929810ff1d}} , within a
generalization of the importance sampling... | m | 8552c5579f0be314f42039709d88f8a6 |
An important question is whether it is possible to define a matrix {{formula:fcdbfa59-b115-4b31-a063-426f292c3def}} of {{formula:83c2fac5-e7f9-442d-afd4-df3972c3b7e3}} such that every graph becomes {{formula:b42c7f83-d32b-4ae5-b608-ee75e366cf04}} -DS.
In {{cite:833623467483671e19bf55a6ac9b5f6e66bbf322}}, it was shown... | i | 69ba565dcea220d3633c94d17c9a0f49 |
Cheng et al. {{cite:b318e837bcb4d075bf98308dfe0029ac52d78173}} proposed an alternative MILP formulation
which uses a variant of the Big M {{cite:f6556c1c86cc5b25eae7009f5fdefc6e83f7940d}} encoding
method for the ReLU activations:
{{formula:f3eef812-5277-4fdf-aa7c-de754f5d0f1b}}
| m | f154e58357aa7a7d14d214b372cc7e5b |
For a graph with {{formula:1c845078-e243-493a-b499-da0008cddafc}} vertices and Laplacian spectrum {{formula:e097719c-502b-494d-8413-5babdb6aee6d}}
it has been proved {{cite:84c521ffa8b7fba6267b672da80362ee80b7b8af}} that:
{{formula:92d00f65-009c-411a-b652-130ab8cb7d30}}
| r | 3c59467b54b91bfff01f7475d8f962c3 |
Canonical correlation analysis (CCA) is one of the most important tools in multivariate analysis for exploring the relationship between two sets of vector samples {{cite:e1a9765ee3727fb1f54ff6b8d1033d4b3d8e3a3f}}. In the standard procedure of CCA, the core step is a regular SVD on the adjusted cross-covariance matrix b... | d | d35cb6d2649f0654beb08df07d907fb2 |
Automatic dataset filtering has been performed to ensure that the training data only contains the optimal observation, action and reward triplet. For this we have utilized the reward signal provided by the simulator and ensured that the subsequent reward only improves from the previous value. This aids in removing the ... | d | c17c5d6358e5f2497dfd8e31593b86f2 |
With the connection of non-negative orthogonal sparse coding to the ReLU function and convolutional neural networks clear, the derivation of the convolutional neural network forward transform required little extra work. The hyperparameter {{formula:2545c12d-a2fe-4658-b923-8949844b2499}} for each exponential distributi... | d | efc05d2342b64129e4c29886a02bb8cb |
BERT
A pre-trained BERT model can be readily applied to the NER task, by reinitializing the output layer size to match the NE labels and fine-tuning the model on the NER data.
We used the case-sensitive version of the multilingual BERT model within the Hugging Face Transformers framework {{cite:047332ff4df50e9d3a7e17c1... | m | bdd6a40915d684cb3bb36f20813c65e6 |
Using one-hot encoding does not provide any useful information about the relationships between the tokens since the method simply assigns an arbitrary vectorial representation to each token. Therefore, pre-training the language model to learn vectorial representations would allow the relationships between tokens in the... | d | defdb6387aa4a9db455d58b2ae727995 |
Limitations
Our work is the first large-scale evaluation of many CNNs and many methods, which we cover three main sets of representative methods: gradient-based, perturbation-based, and CAM-based.
Yet, there are naturally other methods not included in this study.
Furthermore, we tune the hyperparameters of each AM fo... | d | f951c5fd860267c9fcf2be6954ee5749 |
For the data-driven control of unknown nonlinear systems, a common approach is to derive a data-based representation of the dynamics. If the controlled systems are of certain classes, such as polynomial systems having a known degree, the monomials of the state can be chosen as basis functions to design data-driven cont... | i | e26304fe60fee0f98fa7a7973a31702b |
New Paradigm of Designing GNN Architectures. We bridge the gap between discrete regularization framework, graph-based semi-supervised learning, and GNNs, which provides a new paradigm of designing new GNN architectures. Following the new paradigm, researchers could introduce more regularization techniques, e.g., Laplac... | d | 881984a01b9b460d2f7f5c322b019e82 |
Since the objective is linear and the constraints are either linear or linear matrix inequalities,
dual problem (REF ) is a semidefinite programming (SDP) problem, which can be solved by using the standard CVX toolbox {{cite:37fc628e5125ce22e51855629e01aeb05abeb5b7}}, {{cite:eced806fc0a680a157d1bab0ea381cfa4baad8a1}}.
... | m | 291c42a2a984e2f9712bcedb6e5373be |
We take {{formula:338e5e0a-b7d3-48b4-8750-5a713cdaedb6}} by fitting to the total width of {{formula:46f1b25b-7b23-49d8-99a4-fb40cafa4167}} as the {{formula:6fa2aaf0-b51e-4592-97de-47d74ed5a27e}} state. The decay widths of {{formula:39f70830-b7cf-4a7a-9688-0a2c8a358e03}} as the {{formula:6c4795d6-f5cd-4b77-a930-909a... | r | a2d09316569441eb505f4c55ed14dca6 |
We evaluate our framework on Flickr30K Entities {{cite:bdbd3104185abe248785863bd462532316deab9a}} and Referit Game {{cite:c2fbefe4971745686424a49959a04cdeddede1b8}} datasets for phrase grounding task.
| r | 029edf4bad76f6b94991a993a87c4953 |
We evaluate the performance of our proposed FW-based adversarial training (FW-AT) against standard training, and PGD-based adversarial training (PGD-AT) {{cite:1072b743676a36861a03dc5058804e540642abeb}}.
All networks were trained by fine-tuning a standard model.
| r | 192a00fe146663dc1abf6902fded48f9 |
We evaluate our approach on the open-source RL Unplugged Atari dataset {{cite:1fd9075dd3c3059cad3f00b1206d89f35b3a76a0}}, where we show that {{formula:76276038-5694-4681-9771-3dcd80e49400}} -{{formula:b267a422-e68e-4861-876c-eb3e7f812763}} outperforms other offline RL methods. We show that {{formula:15af2229-aa1d-49d8... | i | f1e92a43661b3445d175adcdb52f7942 |
In this paper, we quantify the science prospect of extragalactic HI detections based on a planned large-scale survey, namely, the Commensal Radio Astronomy FasT Survey (CRAFTS). We use FAST commissioning data to estimate parameters including the beamsize, the gain and the system temperature. We make a mock catalogue ba... | d | 61d111f6cf700123f93250febdc577c1 |
This paper presents the first attempt to derive a generic and automatic algorithm for optimizing the control depth of QAOA, which is more efficient than random search and more generally applicable than existing empirical or analytical selection rules. Since the control depth is a hyperparameter of the model, the depth ... | i | 885ad77d7a3a071a4e59d984fcdc8f34 |
We examine the activity detection performance and the channel estimation accuracy of the proposed algorithm through computer simulations. As a reference, we compare the proposed FAT-DL algorithm with the AMP algorithm {{cite:f222dce824c00ed724e3cf29f28aafb4907561f0}}, the LAMP algorithm {{cite:840d2f2fb76705857de7bf377... | r | 508fd1e3cd7d907e7ad071db281cb04c |
where {{formula:a2abd6ce-d0a6-4ca7-85c9-9ab5f56d5bec}}
The above error estimate has been proved rigorously; see, e.g., Wong {{cite:ca47722ff6d9c0818ec55473995350a2cd208e89}}. Thus we have the following result.
| m | 33792248eb59e3255b6b008b54cb761e |
We have noticed that our DSA module gets global context information from features of all snippets by global average pooling, which is same with the squeeze operation in SENet {{cite:fb08437c47efdc10912aa9356c644e5971e2ca1e}}.
However, there are essential differences between SENet and DSA as follows:
| d | 6e2da1e6dfe717d43aab9c556faa7275 |
A central question in graph theory is to understand those graphs containing no copy of some fixed subgraph {{formula:6a4eb4a3-15e9-490a-a6e0-fc084fc88cef}} . In one of the first applications of the probabilistic method, Erdős {{cite:e50f255ad8b6c4dd09dfd9870e0e1328ec8ffee7}} showed that there are {{formula:e08f6947-413... | i | 60b8300a4842ab225aa148634638378d |
All of these systems can be approximately described by a Hamiltonian of Richardson-Gaudin type {{cite:38369014bc7a8a55617e70af50a98edf940ad4cd}}, {{cite:0f7099a38368e24fc1dcfb5578b2ef00a72edf0b}}, {{cite:cba3885e3b08689b7ac948f6ebb6a301de81c25a}},
which is both classically and quantum mechanically integrable. Quantum i... | m | 7e95b680c3a27535005b4bdab99006de |
MAE: We use the ViT-B and ViT-L weights pre-trained on unsupervised ImageNet-1k from the authors of {{cite:9046fd02ce57d1a58f423b5e072958b0fae1f0a1}}. These models were pre-trained for 1600 epochs using normalized pixels as the target.
| m | 4770fff88c7a558157c5c7d0eed09b3e |
We designed a set of four perturbation functions, also called confusion probes, that operate by systematically transforming multiple-choice NLI instances in four publicly available benchmarks, which have been widely used in the literature for assessing machine commonsense performance. These four benchmarks test the abi... | m | 639db4486255f1009ab2f4fbfa2ade09 |
Furthermore, the dynamic communications between IoT devices, EDs, and the MEC server and the migration of IoT data tasks across the MEC network potentially cause security vulnerabilities. blackRecent works {{cite:bd217059b64efc9d3f104b74354a8174db84d05b}}, {{cite:54c7eb186c2c23cfafa1bce36916cca8dbd02edc}}, {{cite:58033... | i | 0bddc2e76c2112192a1aee9de2fff386 |
One of the objectives of the hypercyclic spaceability theory is establishing sufficient conditions for an operator to admit a hypercyclic subspace. This is the case of Theorem REF which can be easily reproved with the theory developed here: for any operator {{formula:1c073746-f799-4f8d-b2e7-90f76596b279}} with {{form... | r | 2344c1db12f849f78d3933212485fd59 |
Next, let us recall the findings of
{{cite:ae6fbf0a6be7811db613dcae8406dfb35292f175}}[Proposition 2] (see also {{cite:c9fa49bc65af4b0fd8b43a1b9124378c7ec8e6d0}} [Theorems 3.1-3.3])
for the asymptotics of
{{formula:3d738952-803a-4432-a09f-c50a593fc554}} , as {{formula:8a0bbfb3-9327-43d9-b893-61dc6c0b5173}} , which will ... | r | b9f95a2c108675416413ed7ef5f52072 |
Unlike LASSO, ridge regression has a closed-form solution without the orthogonality assumption. The solution is a linear function of {{formula:c650b9fe-22e3-42db-9681-3d19371c7034}} and {{formula:dde5a54b-8968-456e-890f-0b0b835d21d3}} given by equation REF . Under the orthogonality assumption, the solution is also a ... | d | 434331e0271dd6dd7f5ba6bf5309bd90 |
Consequently, several extensions are available which include the use of 2nd order information such as preconditioning and optimizing with the Fisher Information Matrix (FIM) {{cite:966da46e6bab7b775b0c294c066dadb7bf077700}}, {{cite:ed4700ebd3d552a7de71b3c924802e92059a021b}}, {{cite:99d45d760581250b6a1e138a47d406ccf6c31... | m | 5cff1a05ae0fd1125d221ab04c4667e2 |
obtained by substituting (REF ) in (REF ), and implied by (7.16)
of {{cite:4f364204333a200b5c9087a726cb6bc4c5e8120a}}.
| r | a4b1badba0b8581bbb84125b4004ac7d |
Let us apply the above mathematical tools to study the energy of fermions in graphene, which is a hexagonal lattice with two Dirac points that are inequal {{formula:2815c709-eba4-47aa-9651-048173c2bfab}} and {{formula:34c4f14f-9b00-4e9c-aa0a-1c4ebc945c0a}} at the zone corners {{cite:201c52f85895d7d40677a14b985bac8c11... | m | cd352adcac6e0a460cecebc8e8ec7e6f |
Classical multi-view methods such as canonical correlation analysis for dimensionality reduction estimate joint information shared by all views {{cite:67bd419dafc1c89308754b883d2e81edaed88c27}}.
Similarly, many multi-view clustering methods assume there is one consensus clustering (see Figure REF below) that is presen... | i | cc3ea764eb941c50ac385fdf2eb72cf8 |
In (REF ), {{formula:4f4abcdc-04a2-41a1-a50c-b14363dabbd9}} is greater than 1, indeed:
{{formula:982d213d-feaf-42d9-9cef-ff760347caf5}}
which is satisfied by (REF ).
Remark 3.10 Here are some connections to existing works where variance reduction techniques are used.
Linear convergence in expectation of the primal-d... | r | 1197c103ef7300345bc5e8757bd490fd |
the mean lifetimes {{formula:503c9c7a-2fea-4d17-aa7e-6dd9fe81320d}} and
{{formula:23761dcf-3df2-4003-8936-972fd95af929}} {{cite:b933226800d0591d72104509a2a5a99ad2fcb82c}}, {{cite:99ac2db0a2ac3c98411e30256ed6589e05d47208}}, and
the values of the Wolfenstein parameters in Refs. {{cite:b933226800d0591d72104509a2a5a99ad2... | r | cf5633ed27a8761f046707a7be67c2a8 |
The present fundamental particle theories are based on Poincare
invariant QFT, and, as noted in Subsec. REF , for solving the problem why a particle and its
antiparticle have equal masses, those theories involve local quantized field {{formula:4fd44668-b242-4cc3-adbe-dc31f78e2c58}} where {{formula:57579dc7-9591-421f-b... | d | 79bc4a3f1ce6eda76aa44299018ca8e6 |
However many methods removing bias from data fail. Removing the column containing the protected characteristic is clearly insufficient due to the presence of proxy variables. A number of methods go beyond removing the column containing the protected characteristic and attempt to de-correlate the other characteristics f... | d | 1ec0f1271e7e0f5c214c612e902e93e1 |
To reduce the amount of computations needed when solving the chemistry on-the-fly, alternative approaches have been attempted. These include a large grid of pre-calculated astrochemical simulations which are then tabulated and used during each hydrodynamical timestep. Although this approach may limit the ability to stu... | i | 02dca0a8e24d51f578ae1c4d78f97781 |
Table REF shows results of our proposed methods against baselines and current state-of-the-art methods at ETH-UCY datasets. Our proposed method Ours-ViT with ViT{{cite:72098b42936316277e4c2d69ed07991cc3f071ac}} feature extractor achieves {{formula:8286bb12-9385-4f25-8460-d226517b0442}} boost performance at FDE metric... | r | dc2892b4284e83d0aed5c7ebad74f695 |
Diagnosis results of different methods: We conducted several experiments for fault diagnosis problem. Our proposed model is trained and tested using two different settings. First, we use Border-SMOTE {{cite:a2d564356e76b2b6c160d5b59ef0df4f43928a1b}} (B-SMOTE) and other resampling techniques to traditionally resample th... | r | 662c7af03082df1ba54381da899f20d4 |
The correlation matrices {{formula:bb01036d-e2f4-48cb-9b25-03d5d588abe1}} and {{formula:c8d5eaf9-8171-4ac6-804a-3d09bade18cd}} are computed according to {{cite:30553f14d6b9c4f7fdb8766403fe87052b41f226}} and {{cite:4a6ad0a4b31cdd3508923fa56f652f17b1e721d2}}, respectively. The size of each RIS element, required by the ... | r | f792731a337f1457817ea5d17d711c3d |
Matsumura-Nishihara {{cite:d5395e0df7cb669ef639b48720f04cd4256e2f18}} showed that the viscous shock wave is stable if {{formula:ef4c1b72-fc8e-415c-b0d4-b5ce4a217eba}} , that is, when {{formula:c05bed81-b088-4a60-89ec-fb771446cdff}} , the strength of shock wave could be large. This condition is later relaxed in {{cite:9... | i | c18419e9293ad0352e3ac462cd907517 |
Baloglu et al. 2019 {{cite:5aa0f14c317dc03b3141e88dfc8ef5f745904560}} CNN+LSTM Epilepsy Normal/Ictal, Interictal/Ictal, Normal/Epilepsy, Nonictal/Ictal, Normal/Interictal/Ictal From Andrzejak et al. {{cite:679219f58a4afe9b829b1e90079bfe77e3a88236}}, 10 Participants (5 Healthy and 5 Epileptic Patients)
| d | a0c545e9c6eb9928beccf51d5bb206c3 |
which is nonlinear and ill-posed (cf.{{cite:ec72cd4eaa65c1b9ab2a7cbeb0020490c12358c6}}).
| r | d787b9cc3b9ce05e53194b3291c8f311 |
is the Krylov space of dimension {{formula:c8dbe57c-232e-4644-bc68-f47c66a7b999}} for {{formula:3df21dfe-b917-4a67-9ebe-9bc0ccf341f5}} and {{formula:898c3403-98cf-41d3-9dbc-8b184567276e}} .Notationally, we let {{formula:fec31cb5-a28d-44ac-870e-5f7bd1e2359e}} be our coefficient matrix throughout, but note that this n... | m | 10964b822b706e7263025a9c6f0ed47d |
Universal quantum computers are expected to efficiently solve several hard problems that are intractable for classical counterparts.
However, to exploit their full potential, quantum error correction (QEC) is necessary.
For current technologies, QEC is highly demanding because it requires precise state preparations, qu... | i | 0763e9c9c030784fd441afee3b8e4c5c |
Adding Groups of Classes Together:
Next, we test our method in a dual task scenario, where {{formula:5f70b38d-c2fd-4fe8-8256-ab833c93d64a}} contains one set of classes and {{formula:15d623ca-194d-48ef-8a0f-090ae4f88fc4}} contains the remaining classes. We consider {{formula:0b79668a-2f06-41e0-b685-a6bae2d92e71}} , {{... | r | 033696e4cab2a5e37309d01458bf7e5a |
In REF , we compare the performance of the proposed JCEDD scheme with different modulation orders, where the power gap factor {{formula:01ba4d23-424b-42c7-ad69-b79ab6d9b7d7}} dB.
It can be checked in REF that the BER increases gradually as the modulation order becomes higher.
Take {{formula:29a3a3e5-049d-4bdc-bf81-... | r | 06854a2ed94dce7f947d97df48330e08 |
{{cite:6629ab8762bf33f50e9cc1b3cbf3a5d36b7f113f}} have suggested that {{formula:17759ac6-e8bd-4132-9cb6-fb74d01984d9}} is a BLR metallicity indicator for SDSS type 1 AGNs. {{cite:e729af1888654ad3d273f435695d69aaa843cd0b}}, {{cite:9cece8e12e7056ff854e1082c143f57e9e625cf0}}
have suggested that {{formula:3b3eb492-6b0f-44... | r | 2f7843006e93e6c140dd13db448b4039 |
It is straightforward to see that for {{formula:2f584b05-fe46-458c-9812-ce943751996a}} , {{formula:836ab529-aee6-4bc6-bec1-dc67066eb831}} reduced to {{formula:ebb4fa2a-4d18-4bd1-8288-be0f2f476ae5}} by using {{cite:a60e8f38332dd4293c2b0fbb2f196b389404d6f5}}
{{formula:e1ccd61b-b23c-43c8-8dbe-70fcab7636c3}}
| i | 17de8ca3a468422e66ed0204008629b7 |
On that path, SLAC is planning the E320 experiment, and DESY is planning the LUXE experiment {{cite:4dfd250fe64b18f50f3fb73098372d0ff7069fc8}} using conventionally accelerated [10 or {{formula:805fb323-0237-43dc-b91c-7c04ece66784}} ]GeV electron beams in collision with tens of TW laser pulses. The University of Michiga... | i | 9e20074c24bc61e8dbdf7f995a912c97 |
If we consider the back-projected pixel-level features as pseudo 3D points, our loss function is similar to PointInfoNCE {{cite:a932b2a59d8799d1206dceb06151990dd0d7e31e}}. We both apply contrastive loss on point-level (or pixel-level) instead of global instance level, which is commonly seen in 2D contrastive learning. ... | d | f8a319349503f63fd8e1878b583cd7b2 |
Black-box evaluation: To evaluate ATD under the black-box setting, we generate adversarial perturbations by attacking the introduced baselines as the source models and transferring them to the ATD as the target model. This test can also be considered as a sanity check for detecting gradient obfuscation in the model {{c... | r | e64ce6f443e5e1e750470151183d223b |
Fe{{formula:bd8b65bd-c92d-4790-9108-1bd5fa2817f1}} N{{formula:001ed26e-5b38-4334-91d5-f30274216116}} has a body center tetragonal structure with space group I{{formula:3c835263-ca70-4adf-a11b-d17da3812f32}} (number 139). Our PBE optimized lattice constants a=b=5.68Å , c=6.22Å and position parameters, x{{formula:ef8f... | r | 0e1b0eaf4298088363909db91a372117 |
This phenomenon of low stability must also be present in other finite
geometries, like cylindrical structures that have been proposed
recently {{cite:e5f4b755bc2b2e79462024140cb7fe6da4cf72f6}}, {{cite:be2a63ec84b6cfc3bd138fe8e1a28e7c2b6dac45}}, {{cite:35c85c012959732007213c0fa97fda02272aef7c}}, complicating any technol... | d | 18c151a9b61a314af97c79949813fcc2 |
where {{formula:f00df8e9-2150-4bbc-b8f9-30b9acea44a3}} is the estiamted number of people, and {{formula:171cbd2b-a4c7-423a-876b-34e543e3166b}} is the groundtruth number. We pre-train the front-end on ImageNet {{cite:cc687745cdf3ab0c11efc006ea6b12701d89e966}}, and then train the benchmark network on the crowd datasets... | m | a8d9fec10ca28e554e4f417a7906a8b5 |
Writing {{formula:28fa0b74-5b7b-4b69-a427-7961c99f98f6}} for the set of discontinuities of {{formula:2b664727-20d4-4b09-966a-c31437503c77}} , we have {{formula:53cf9bec-4809-4b7c-badc-b550ff80e8a3}} by assumption. By Skorokhod's representation theorem {{cite:b384df7a8580ba32271f90802f65e712921c82f9}}, there exist ra... | r | 8c6b21af80bd327bcb65baafb9c79cd6 |
We study different versions of local search on variable orderings. In contrast to previous work that defined the local neighborhood of an ordering as all orderings that can be reached via one operation, we consider parameterized local search {{cite:7766c6b47d938791bb9c7bd130011c6e0740d7d0}}, {{cite:a24b07e64cfc4c48b7b7... | r | 4578e8d31365efd097d564ac32eca1b8 |
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