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In this work we have proposed a protocol for PV, referred as {{formula:80d19f30-6b17-46ff-9c81-e22b0dfa2195}} throughout the text, and proved lower bounds on the quantum resources necessary to break it. Our bounds, appearing in Theorem REF , do not answer in a definite way Question REF and, in particular, are not eno... | d | e87ad116d22e0e8757df0fc544f538e7 |
where {{formula:e80526c1-7f1d-44ab-88cf-74247bdc1169}} is some subset of {{formula:3345b8f5-8e71-4508-9784-3bc756348157}} and {{formula:18984be6-ace4-4ed7-9c43-f2aa42bac6ca}} is some sequence of coefficients. A basic version is to have positive coefficients {{formula:f9c4b109-3e40-4331-b2cc-8d79427944e1}} such that... | m | 06db3a2875e6cf6bd30bd546750edbab |
In general, domain decomposition for uncertainty quantification and inverse problems gains a lot of interests, and related methods are actively developed. In {{cite:541cf0e9e88468106b08a1d216fc3d4eb00b181a}}, local polynomial chaos expansions based on domain decomposition are proposed for solving PDEs with high dimensi... | i | 2acd6c6576bfd37d36f8f7d35b96ec3b |
The idea of analyzing PPSZ assuming some non-uniform distribution {{formula:03d11081-2964-449e-83f1-069000431241}} on permutations and paying a price
in terms of {{formula:c476ddc9-709b-4f5f-ade5-0c110c6c2247}} is not new. It is explicit in {{cite:77e45d637e9b047cfabf8315bf8e42976795c021}} and implicit in
{{cite:6ce2... | i | 23d136b9beebd964b5ed075db30bf3e9 |
Now consider a more heterogeneous network with {{formula:e4d71afe-fed1-4a54-b184-b471efc2bafd}} and {{formula:f4e81c31-dacd-4a40-8a14-910b06e11dec}} ,
i.e. well above threshold so that most neurons would fire if uncoupled,
again with {{formula:adb1c3d9-3b73-432c-b102-fe1ddcc5fa61}} and
a uniform degree distribution o... | r | e7a5f53fbffc242b0b6a77277ef48e72 |
To identify conditions in which machine learning with existing quantum annealing devices may be of use for studying a simplified biological problem, we report results obtained by solving a learning protocol with six different strategies: (i) an adiabatic quantum machine learning approach formulated in Refs. {{cite:d48e... | r | a626aa6fa195d9cb7dcafccf70534fbc |
We first observe that for Hamiltonians with evenly distributed magnitudes {{formula:2f383f97-f6b6-47db-9831-6b65577475bc}} , the only benefit of our modification is the finer control over the total gate count. By construction, whenever {{formula:ec77eeb3-c0c6-46d4-af32-9c1b532f3add}} , {{formula:82436f33-5e20-4b2c-aa07... | r | 4b600ae56f6ed1846ea193d0adbdec53 |
As a final comparison, we have also checked whether the forecasting performance of the DeepAR model is superior to that of an alternative model such as the Gradient Boosting (GB) model {{cite:8b906bf794480314dae722fd92cb4813579fc2a8}}, {{cite:fc7dac1377dfba7915b3ec6031c61512fbdbe990}}, often used for financial applicat... | r | df817e2629c74779a84c61fddd607d4f |
We focus on multiplicative weights update methods that use an exponential multiplication function, as in {{cite:03e06e8e1b7cf31aca30e8c19ebe8254566b96cb}}. Below we define one of the popular versions, that results from the FTRL dynamics (Follow-The-Regularized-Leader), when the regularizer is the negative entropy funct... | m | cff897c43a596a9ab15186cf9b403098 |
Relation to other research: Having effective tools for interpreting networks has been a key goal, especially when this aids in the diagnosis of failure modes (e.g., {{cite:5e888c4e41af254cac15bf7e356d3b8c5696756b}}, {{cite:d90fff7d03db639fa7a7338ba688cbc0edbacbf6}}, {{cite:cc36f770c31c227e5ce855227e5b844d6482a4d9}}).
O... | d | de32fa1dceb0deb028c226f837e44f86 |
We have extended the recently proposed interferometric WVA technique to amplify tiny polarization anisotropy effects in a more practical scenario dealing with simultaneous exhibition of multiple tiny polarization anisotropy effects. Polarization is used as the pointer here, whereas, path degree of freedom of the interf... | d | 81f78b6e424df90e0322dab3af548da4 |
Generally, traditional stereo matching consists of all or portion of the following four steps: matching cost computation, cost aggregation, disparity optimization, and some post-processing steps {{cite:f8660ef671bfb1ed246d0ac3c0d9d54b9047fb30}}. In the first step, the matching costs of all pixels are computed for all p... | m | 37d5666f2ef04fe85a9f2aba4bbb679a |
where {{formula:cd064143-1c15-4933-8dc8-d0a8078f5fbd}} denotes the entropy of {{formula:2f4340f9-09ff-4baa-9054-c625d56b4918}} and {{formula:f21a3973-5f89-48b7-b17f-86e03aff0be6}} is a regularization parameter. For very small {{formula:a5b113c1-3c76-432b-af49-8fccfa8aee40}} , optimizing Eq. (REF ) is equivalent to o... | m | ada78f9bf89dd4e16f8e049f11384b35 |
Sequential recommenders trained predominantly on interaction data from core users often fail to capture the activity patterns of casual users and, as a result, provide less satisfactory recommendations for casual users. As shown in Figure REF (b), the self-attention based recommender (SASRec {{cite:6acb66fcd49030d0ba28... | i | 2e79580dbed1347356649e5b2fc283d7 |
How does MVG work on datasets where motivating characteristics from Figure REF are absent? To answer this, we use the popular MSMarco {{cite:d3ffc769be296aff5db715354da00d18c26c27ee}} question-answering dataset which has flat document popularity distribution, likely due to synthetic curation and heavy preprocessing. T... | r | 451a0baee7919a0d0a4c126ced77b3b7 |
We compare our method against a number of recently proposed state-of-the-art ZSD and GZSD methods. These include: (a) SB, LAB {{cite:2f20188d27a649f892287a2f3168bf61f3954beb}}, which is a background-aware approach that considers external annotations from object instances belonging to neither seen or unseen. This extra ... | m | 584dec5262c2327fa12ac4b3cb5a4259 |
(2) Is it possible to obtain comparable results using BERT model pre-trained on smaller-sized data? We present results of the experiments that were conducted using the models pre-trained on the PubMed abstracts only. These results were comparable to the results produced by the model trained on the PubMed, PMC, and Pubm... | d | 625238d59feaf1360fe61724c4d20098 |
The paper is organized as follows. In Section we derive the structure of the physical part
of the flavor non–singlet unrenormalized off shell OMEs to three–loop order. From their pole terms of
{{formula:13a0cb00-5930-4c82-a8ec-c3f1219669f2}} one can extract the non–singlet anomalous dimensions. Due to a known Ward id... | i | a39e1230bdf968110f78a78cc31d4e02 |
In this study, we trained artificial neural networks using a novel spectral regularizer to further understand the benefits and intricacies of a {{formula:430c3a41-e693-4c47-b9b9-c088f14654e4}} spectra in neural representations.
We note that our current implementation of the spectral regularization is not intended to b... | d | 7df8c620d4d1298b002643c5d537b29f |
The likelihood ratio test (Sections 9.2.1 & 10.3.1, {{cite:d3515a194d6b679ed483a7a769b483eadb9c530d}}) compares the likelihood of the data based on the MLE (i.e., the maximized likelihood estimate) to the likelihood of the data when restricting the parameter space (which in the notation above can be expressed as settin... | m | bd7f98e53385e5a6c2330dc44cf0ac25 |
A limitation to consider is that the realistic samples used in the training set for the defense algorithm can be expensive or difficult to collect.
Moreover, in realistic scenarios, an API to a black box may be costly to query with the perturbed samples generated by explainers. In practice, explainer queries should be ... | d | ecd2f861da70d904a81bbf3e731d42f1 |
Proposition 2.4 {{cite:041413298a386b1dfc5b20d3e480b85131db7eb7}}
If {{formula:8fc38a98-48fb-4721-86cd-15f4b5bc2432}} is a graph with {{formula:1291fe0b-a973-4600-9185-d8825eb3b08b}} , then {{formula:4f24564e-c8be-473f-8245-d532f32f09da}} .
| r | a910af8feed1234a97b2c19aea8cdc8d |
Prior works like ADAIN {{cite:8e3083483aa7eb1a4da9d182d4aed2c86a7a770f}} have leveraged attention-based mechanisms to estimate AQ. But, the deep neural network cannot capture the notion of uncertainty. This limitation can be solved by using non-parametric probabilistic machine learning techniques such as Gaussian Proce... | i | 3f0ecef1fc1ebe3e418c9113d3be023c |
Data generation is an important field that aims to capture the inherent distribution of data to generate similar yet new data. It is a long-lasting, fast-growing important field due to its wide applications in critical fields such as molecule design {{cite:be221956d421c90458e2ae9748ffb8109405e4d7}}, {{cite:4afc3b265658... | i | 08c044e2a6dff27d1e000dddba86d1e1 |
Recently, topological insulators (TI) exhibiting Rashba spin-orbit splitting (RSS) due to the presence of 2D electron gas states have been recognized as key materials for next generation spintronic devices without the requirement of an external magnetic field for manipulation of spins {{cite:1540ef14fbc34dcbfffa0d7e9ae... | i | c30c983d99ca14b90cf6c3fee7dadd73 |
Server:
{{formula:36af885d-31a3-4618-b851-990593ad3e31}}
{{formula:1641d583-cc40-4e02-9a85-ac331a8cb055}}
Assign clients to clusters {{formula:5d1448bb-e604-4340-8872-1e5b65e999a3}} with {{formula:d5f6c5e5-b070-4f6d-84b2-386aa48fa9f4}}
Compute secure average {{formula:7d3c706e-a662-43d0-b3d6-35b5c6864e62}}
{{formu... | m | 0470cccc7b11c3d3c1bde07cc0959bd7 |
Condition e) implies that {{formula:4c112844-049d-4261-9723-14499fc5aef2}} is a small set, in the terminology of {{cite:e667754f1dbc72610c88d77fbb74c4de385be1e5}}. In view of conditions a) and c), we may apply Theorem 11.3.4 of {{cite:e667754f1dbc72610c88d77fbb74c4de385be1e5}}, thereby ensuring that {{formula:97e7236f... | r | c712a54c6f95a18ef98a4686f30fb933 |
We compare our results with prior works in Remark . We also show that Parameterization REF is inherent for spectral sparsification.
In particular, we use a hardness result from {{cite:7d3656d5851bbd9933e8a7fad4a7b9597b976ac9}} to show that for the Gaussian kernel, under the strong exponential time hypothesis {{cite:42... | r | 98291a2cc2a992588c2cc06f23575e31 |
The effect of the fixed and degree-based number of random walks is tested by using three different networks. The first one of these networks is Zachary Karate Club Network {{cite:73141357f85eabfd2ad8f7c1ba746debda3e945c}}. This small and well-studied network is used as a test case and also a platform to discuss the imp... | r | 865f79cb2e6eb4be5ffe3d789956e342 |
{{cite:5d3953b1221cba53b36236ed89ad874dadee4acf}} find a similar disk transition in their 2D isothermal hydrodynamical calculations, which sample a few different eccentricities and use the same fiducial disk parameters but cut out the region of the domain containing the binary {{cite:3adaeff47da11291748c9feedafc842153f... | d | b32d52d013c34f6582f3ecf01d46203a |
The low-density parity-check codes, (LDPC), first discovered by
Gallager in 1962 {{cite:12017e2b169d517cc6187fc68e9b7b8986e200a2}}, were brought up to date by
MacKay in 1999. These codes have a parity-check matrix whose
columns and rows contain a small number of 1's. Like the Turbo-codes, they achieve
information rates... | i | 6d2ee68cd29ca39febef872958f226b2 |
In the following sections, we derive our proposed loss term from {{cite:7c28df80cabcea0947f2a193e6a31db5de748fef}}, {{cite:b78c2f5e2d50cccf6149424e089c7d4e2318cb26}}. First, in section REF , we derive a similar loss term which we name as alignment loss from Tiao et al.'s {{cite:7c28df80cabcea0947f2a193e6a31db5de748fef}... | m | 8282f93e72b4c61f3beecbe818dd4bd5 |
On the other hand, both GIRAFFE {{cite:8acd0c88046ed62141201dcd9d3af5512fbbc641}} and 3D-SGAN can effectively disentangle the different variation factors. However, GIRAFFE {{cite:8acd0c88046ed62141201dcd9d3af5512fbbc641}} suffers from multi-view inconsistencies and mode collapse for texture generation. Compared with th... | m | c896b6ac57ec72a29a7faaa85fa1ea7f |
LSTM(Long Short-Term Memory Network) is a well-known recurrent neural network and has been shown to be very suitable for sequence prediction problems. To do network reconstruction with LSTM, previous work {{cite:010ba006d7e645a1ba94d3c640823f4695271eef}} used thresholded correlation matrix to represent the adjacency m... | r | 3905d4705345cad1180a722c9805846d |
However, the infalling multiphase tail is not aligned with the jet axis implied by features consistent with E-W oriented X-ray cavities observed in the Chandra data {{cite:ee1cdd0e4886533a53b181758f26fdd32da9ffb4}}. This indicates that the gaseous component either might have originally formed at the interface between t... | d | 91537082b7ae0a8c344efae9dc772126 |
There is still very little known about the nature of the dark matter in the universe, besides that it is non-relativistic and interacts only weakly with the Standard Model. Whilst it is typically assumed that the dark matter consists of some as-yet undiscovered elementary particle, primordial black holes (PBHs) are a c... | i | 7ffcb906237ee8dc065740c69ebf16bd |
where {{formula:b2c88b83-5e26-441f-9b78-e6fb2b35466b}} is overrelaxation and {{formula:a8566969-584f-4531-8626-b5083378325b}} is
underrelaxation. For {{formula:14aeb460-d5cd-45a2-bdc7-7476ec4f7eae}} in the whole range from 0 to 2 and any {{formula:cf003f9c-e92b-48c2-9062-4f1705f07c30}} it
holds that the iteration c... | m | d0c2ec3523912df479229c5b39490511 |
Backtracking is an inexact line search technique typically used in the context of descent direction algorithms for solving non-linear optimization problems {{cite:16cbd74d76e6d350415116fc0b2e5f38198248fb}}, {{cite:5c89027aa89791981baa90b2cd6b730d45c1841a}}, {{cite:6f589138583d3c5d7e57b01e00369687b91e11c9}}. After a des... | i | 4b586ad5d690e7c95ad440a91659e38a |
Currently, cosmologists have been interested in the models covering a larger domain in the thermal history of the universe. In this way, the models that can describe both very early time and very late time accelerating expansion of the universe have attracted a lot of attention. In this respect, in some viable models o... | d | d0af80e503f1bd3dcefd53ec4b67ecb7 |
For example, matching with preferences typically assumes that only ordinal utilities can be elicited.
Ordinal utilities provide only the rankings of utilities received from different bundles of goods or choices. It does not require individuals to specify how much extra utility they received from the preferred bundle of... | i | 6605ea38a843e5f5f62d31020a485272 |
Alternatively, {{cite:3b574f9121c9d85447a41e56d2ad28a4995b3892}}, {{cite:26a9db9f2765cbd37f0d677c5ffa603d451437de}}, {{cite:72207d12e150df4a1f4a186f1a02e413a278307c}} proposed turbulence inside the
jet as accelerating mechanism: flares
are triggered by the passage of turbulent relativistic plasma flow in a
re-collimati... | i | c064d37027c156f45c2f193098fe722c |
paragraph40ex plus0ex minus0ex-1emReDO
We provide results of ReDO {{cite:4b7791768752ecea81996a428e746eff2636a5ec}} on birds dataset and tmds dataset, shown in fig:suppredo. ReDO overall performs better than GrabCut on birds dataset, while it may fail when the background regions become more complex. We can also observe... | r | 003b895d8574ab7dd571468e8baa5327 |
The one-loop matching for the {{formula:faaf06da-f47a-4868-94b5-a1390e385f24}} model onto the SMEFT,
up to dimension-six operators, resulting by integrating out the two
scalar leptoquarks at a scale of the order of their masses {{formula:1857b107-e66c-4acc-9a64-8a5bce979d03}} .
The complete set of matching conditions... | m | bf5e69c6d27855dceaf6aa1a6533eb02 |
Among the fission barriers, the inner one is a crucial physical quantity used to determine the neutron fission cross-section of actinide nuclei since it is higher than the outer one for most of the actinides important for energy application{{cite:87d5ceb1ab83b3dc3edfdb7ca3729cdbba589ad2}}.
Traditionally, the inner fiss... | i | b7448a4fc5c29464580609b276e9049e |
The following lemma shows the log-convexity of posynomials {{cite:6ee19527f5874404abe84f1d872fed678d9ab1ad}}.
| r | 97ec7d810daa3533c0575be4fd20f9a5 |
Non-convex non-smooth losses. We conclude with the case of weakly convex non-smooth stochastic optimization, where we devise algorithms to compute close to nearly-stationary points. Weakly convex functions are a natural and rather common model in some machine learning applications, including convex composite losses, ro... | r | 8f17edf05df26e9d4e9d52bf874314bc |
Bayesian methods {{cite:21c0269ac9d25463c472681ba4ca9f3cb478ecef}} for model estimation were also not used in this study. An important fact is that Bayesian methods provide an alternative path to estimate the parameters of a choice model, not fundamentally different models. Theoretically speaking, maximum likelihood an... | d | 98eaa9a8db210652577c6a16cc3d249c |
We have demonstrated
an on-chip microwave photon router that can be switched in-situ between scattering photons back, forward, or symmetrically in both directions.
While it is limited in dynamic range, it is fully compatible with modern superconducting quantum computing devices {{cite:cbf894cbb4b80bad86d2f3ecdf5266b7fd... | d | 2c32e7172c302f3c2b1f9bb894fcd6ae |
For a general
set of nodes (REF ), {{formula:031dd8fc-f4d9-4a4e-9429-012f933e50ff}} represents a simple Riemann approximation of the corresponding integral, which has first
order of accuracy, only. If, however, the nodes are chosen as those
of the Chebyshev intergration, the orders {{formula:1c802a65-0b85-4328-9230-05... | m | c858bed5683d2a3a78ad187fa4c8f6f7 |
PyramidNet {{cite:f8972acfc500625312b267a1aa49693a6173f719}} {{formula:5947307c-0ac9-42d3-a1b9-cad5ea8a10e0}} {{formula:0fea9e8e-d0b2-40b3-b51c-401f7168b678}} {{formula:97e9ddcf-4ae2-4499-9a9f-e77002871d03}} - {{formula:c7222947-fdbf-4187-82b2-82b4947f6953}}
| r | 3e3dad75202f20755f81723c3956e9df |
For comparison, we also repeat the above steps to the standard Transformer {{cite:63df401c6bf05009574c8e0e1b162f61bd1d0585}} only with the Softmax attention. For simplicity, we denote the optimal architecture of the cosFormer as “cosFormer{{formula:ee327042-ef2f-4b19-8419-db32cfba7284}} ”, and that of the Transformer a... | d | 749b5311f4872833e2a0e135e0da8966 |
In this section, we study the Born cross sections of {{formula:b5974a5b-0b1a-4e29-b291-389c995b5207}} {{cite:132b01f2042fe1df1ef31d8ac8a257d6e41b925d}} and {{formula:479d6ba0-a8d3-4032-b503-3f462f97704e}} {{cite:f268b29547071c4e907c72234ba78be973837669}}.
As a first step, we need to identify the contributions of diff... | r | 46e2070aff6d6554f6bc1e4345e1df1e |
Machine learning (ML) has conquered intricate tasks in the past decade {{cite:bcac08182fbbc3cc0dd8d96e7ae40d6fd4f12ba2}}, {{cite:37612794ec458cd4c28c9e82351f557b0b8dc0e9}}. A critical obstacle to applying ML is that collecting sufficient labeled data is both time-demanding and resource-consuming. Consequently, model tr... | i | 0f1852ec6dea6505994fcc56810ee4cb |
Videos can be treated as a special kind of sequential data, which are appropriate to be modeled by Recurrent Neural Networks (RNNs). Ranzato et al. {{cite:317508dde48424ca56451f6ed124500cf1293466}} first utilized RNNs to model the spatiotemporal dynamics for videos in an unsupervised manner. To fix the gradient vanishi... | i | dfdea6fc38ee18be169d4546b81752ef |
In this work, we have carried out a series of {{formula:5c9bf05e-b22c-4a22-b8f8-0be6ad4b1ccb}} -body simulations of star clusters with two components (BHs and light stars), which approximates star clusters with top-heavy IMFs.
The simplification of the {{formula:e9b097d5-db53-4653-a070-cb80cba56a83}} -body models allow... | d | 2787520585fb673d531d872b5c72e491 |
We use Resnet-50 {{cite:032f625f27aba09109ce3b4c47f9959ea6bf3c73}} for a base network. We use it as is for Baseline, ODIN{{formula:295ec6b8-33f8-4012-b6d7-14e9ec27928e}}, and Mahalanobis, which share the same networks with the same weights, which will be referred to as Standard. We apply dropout to the last fully-conne... | r | 4c0f112ec77be3deac5f4042529edbed |
In this section, we use the observational data to reconstruct the ionization history of our universe and put constraints on DM annihilation.
CAMB {{cite:37ebc49e35db6614425bad5ca75c36f78dcaeda8}} and CosmoRec {{cite:2a7aba8a40b9c3ea0687d1deb3903624d3987460}} are used to calculate the optical depth and CMB power spectra... | r | a9d0a4fa3303b5f04591197d2bd5c656 |
The keypoint-based methods are generally more accurate compared to the direct methods. It usually uses DNNs to detect 2D keypoints in the image and then follow a Perspective-n-Point (PnP) solver to get the 6D pose. BB8 {{cite:8c3cf863dda381cc46172ae9e494775e6ef1fe3a}} firstly uses DNNs to segment the target object and ... | m | a377a6d531ea1dae773fe28851ab9154 |
The underlying architecture of the DEM model is a fully connected feed-forward network, which is similar to the one depicted in Fig. REF and was described in the work of Nguyen et al. {{cite:9bc8d47d70d2f302b831a3be990860df3bbb6804}}. Fourier transform was applied using the package Random Fourier Features Pytorch (RFF... | m | 64acec0c53443b9ad2e0b7e8337da24d |
Multi-unit prophet inequalities. Since first posed by {{cite:3229b2f5a80fcbccd1c18851c7869ce1055b9436}}, prophet inequalities have been extensively studied (see a survey {{cite:7a7b0675b012ad0ffa6438893d5af90e72cb7ae9}}) and in recent years, there have been a lot of working studying prophet inequalities with various fe... | r | 8afb3ea569dc1f04ddef33e074b23640 |
The interpolation method is a rigorous technique to prove upper bounds for the free energy in various models. It has several variants. Originally it was invented by Guerra {{cite:630ac0b241f91e70e5cc83f1684bfb29f14ccd8e}} in the context of the Sherrington–Kirkpatrick spin glass model. In this section we explain the tec... | m | 92ee8887aad8a8816f47c0e4b35f4e83 |
then, the continuous mapping theorem (e.g., {{cite:8d7823d7bfa3551bbd7693fb04058e49aa57e988}}) implies the convergence of {{formula:b7ee625b-445c-4d21-96e9-c234e67622c6}} to
{{formula:1213c12c-022d-4658-b37f-375afebbccc4}} in distribution.
Given the convergence in distribution of a sequence {{formula:9799f845-6766-46... | d | 55e441131cfd3129ce3201ed2ef75e22 |
Motivated by the sampling of the incomplete missing data approach for deriving full posterior summaries, including uncertainty quantification, and motivated in {{cite:11bf2689f045dadeefc0bb4d488d920e21deca5f}}, our idea for estimating the Bayesian MDP model is to use the simplest algorithm currently available, which is... | d | 1585b9b10f8611c1dda4f8521ddd9f99 |
Extension to verifiably robust models: An advantage of our simple framework is that we can incorporate methods from the adversarial examples literature for few-shot learning. Specifically, we consider verifiably robust procedures where the goal is to provide a guarantee on adversarial robustness of the model. Standard ... | d | 1f8509186274d8673cdd656b98e671f7 |
Implementation and Training Details.
Table REF lists the important architectural details of our MuseMorphose model.
For better training outcomes, we introduce both cyclical KL annealing {{cite:64b07573750566912155e98d9dd0587db84ce4a1}} and free bits {{cite:98746014c1d5e73e66e674ff0f11be0bfc357dae}} (both have been int... | m | bd1d0454711e3c435603f5c65b0d381a |
Our approach is based on a
method proposed
by E, Jentzen & Han {{cite:8102bede845a77509d289a2640b2a877f4da2ff6}}, {{cite:c20f1b7a929a7ae76bc0615314172375a044a6ab}},
which we call
deep empirical risk minimization (deep ERM).
In this framework, the controller is replaced
by a deep artificial neural network
and the random... | i | 3e2c0eb033e6b603e7d38138bb2a3035 |
We use the algorithm designed for configurational sampling; a correction term is given in {{cite:74ed96723b322c9c8d1ead443fa6b985c9ef6f66}} to improve the sampling of momenta, though this has no effect on configurational averages. We must initialize the {{formula:8afcefa6-8c2f-49ac-9b06-8c43ef96491d}} –vector {{formula... | m | e6cd70ef8f9457541da10f6cc4f02cd5 |
Complex (dusty) plasmas represent a distinct type of low-temperature plasmas that consist of highly charged nano- or microparticles {{cite:8b83c7c5891c83494bb22570d3e885dcb0a95ff9}}, {{cite:2578420a26c2f8aa947cf131e09d64371345c116}}, {{cite:b3e031c1a46a49a83549275f9fea32bdba273084}}, {{cite:422eca42693195147c0a1824bdeb... | i | 80d64a7ec5005373b3426828dbc991e3 |
This is achieved with out of context sampling (Figure REF ). NP sample a set of observations for the context {{formula:58b3b83e-8fb4-4847-9271-f8d8f455aebb}} and target sets {{formula:45c65e6f-bce2-48cb-9076-8064a2c56db2}} . The context set is used to generate the representations and the target set to verify the predi... | m | fe7f57543b80f4ce5d15c98a170dacca |
Additionally, our proposed network significantly reduced the false-positive responses. Conventional deep learning networks {{cite:ed90263218b6534e669f86811ba4f8c41b49b9b7}}, {{cite:a2607281db932f163be0d1b396395259ef3bc3d7}}, {{cite:2103068adbcec83fce322483336e23bfdc5d0aed}}, {{cite:114fadf5c50fe759e1f04578ca926162a7888... | d | c1b5206c0036a5bf27e9ec83fcdbe093 |
where {{formula:950bd2a7-1e3a-40b1-8769-a1fe03864a3f}} are the three complex angles of the orthogonal matrix {{formula:69b1c9ad-2854-4306-a4bb-9e4da932998d}} in Eqn. (REF ). Explicit expressions of {{formula:1a3d992f-8224-4b15-9cf7-4db4847a94a2}} can be found in Ref. {{cite:a579c0f07b867f12e1d3e32f3ad5030fb80cddb2}}... | d | 3ae5f48c46d6ba03926f79301f60a9ad |
Let us calculate the probability that after step 1 there exists an
unseen value {{formula:209e5288-1cc8-4e18-97e7-366297213880}} which is represented in at least {{formula:510abae9-76cd-4e0c-886a-e59bc9b0609a}}
variables, i.e., {{formula:5cab6c6b-93ef-4df7-8263-b714f8de59b1}} .
Consider an arbitrary value {{formula:2... | r | 404896e6453a25e2ddcc9bb8fe047d17 |
Recently, Want et al. {{cite:b4391aca33622e8e14125c8be61ff24609226b4e}} shows that merely pretraining an embedding function on base classes along with nearest neighbor clustering in {{formula:49705017-84cb-43c3-85c7-d74d7d904535}} distance can achieve competitive results. This line of work avoid complicated training s... | m | 874d21723b37d1aaf7d63ef6e9b8263a |
Although there are {{formula:8f7a1230-666d-4c48-bef9-b6d3e7d9f9d4}} -analogues of Whipple's well-poised {{formula:5d8f6eba-9c28-4601-8931-19256ea33a0c}}
transformation and of Karlsson–Minton's summation
(see {{cite:3381aca3a6e367974a66f741f8d34fa8d78b6e28}}),
we are unable to give a proof of (REF ).
This is because we... | d | 115001b58c93bdb44474427b3f9a515d |
Pruning aims at removing unimportant weights/neurons to slim the over-parameterized DNN models.
Since fully-connected layers contain the dominant number of parameters in early stage of the classical DNN models, research works focus on removing the neurons in the fully-connected layers {{cite:33f14d8e1587ba8922fd0a18b52... | m | 0c020a02387672e2adfb7eaa259f342c |
Researchers had used traditional machine learning methods before creating deep learning models. Although these methods are still in use, they have become limited to specific applications. An HMM model using combined dynamic texture as the feature set {{cite:310cf66128a1c357da153c5e66020e756e3ebb3d}}, social force metho... | i | e1931cbc273c98e44428f0fe0388a5c0 |
We set the number of nodes in the mesh to {{formula:cab1fe77-e705-4a10-b58b-14bfd55e937c}} and consider observations generated from the solution to the PDE on a finer mesh at 81 random nodes with {{formula:06563ea9-b8db-4f47-9289-a416644d2ee9}} chosen such that a prescribed signal-to-noise ratio, defined as {{formula... | r | 9a51261845d852d6f755e97193b16445 |
Another interesting result is that the two-stream RGB-difference model shows the performance that is close to the OF-based model while saving a large number of calculations.
These findings correspond to the results of {{cite:4aaab10824108cfc4b350ad2c087e31716278966}}, {{cite:4fdf9e9e48bc81b6b3a9266dd5f97dd33315c89c}}. ... | m | 67164cd82d1ca8940447520c46f53348 |
Combining three unitary matrices {{formula:5c262b60-e87f-4641-8413-74072e23503f}} , {{formula:f58a40dc-b674-4809-a0e8-762201d360bc}} and {{formula:b6d2e424-c402-4a6a-be82-b8b1f46f21f4}} together, we finally obtain the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) matrix {{cite:1eab77b81127fc11067362515aa3bde63728b9ec}}, {{c... | r | b2560231b4fa5721d8752a369adbd792 |
Carefully adding noise to specific parts of existing algorithms is a principled approach for developing differentially private algorithms {{cite:91b5391d2f8935238233a8ce0aa5c5704613f80d}}, {{cite:9ed517e20931132f9818723e45cfc00fcb9eb9ab}}, {{cite:a8815cfb5479352aed8c7375e3fda5857efdd87a}}. The main challenge in such an... | d | e9d22f6bc63e8e22b718ee7685895026 |
The next lemma presents an equivalent description of semismoothness{{formula:1467391a-d778-48db-a063-bf7eebb25d7f}} for Lipschitzian gradient mappings. This result follows from the combination of Proposition 3.7 in Gfrerer and Outrata {{cite:fed4e5b12f03b281ee264c9f51b939ae3b5ef5ca}} and Theorem 13.52 in Rockafellar a... | m | 28f84a2b7e46bc7295601c539b1b6b94 |
It has recently been noted that Donoghue's S-matrix technique can be
short-circuited to produce gauge independent effective field equations
directly, without passing through the intermediate stages of computing
scattering amplitudes and solving the inverse scattering problem
{{cite:36cb98ca1c05274762cb9064b358debce559c... | i | d66a1cf2c8ab5e0c6034f129d5589492 |
It is known that {{formula:d99e8198-cb76-4127-aab1-fad8df7a16ae}} is a proper subset of {{formula:9f952eff-0391-44e9-bf48-12c079330e83}} and we abuse the notation without confusion that
{{formula:c919f9b7-e859-4d29-9dd0-0b6de6af6445}} when {{formula:76831575-9d67-4864-8009-f7dc5ae718a4}} in the definition of very w... | i | 524082d6127e4bf25be236d3e79e9f6e |
Recently, the high data-rate requirement with increased capacity and bandwidth direct us towards the free space optics (FSO) as an efficient
replacement to the RF links. This is because of its easy deployment, low cost, and point-to-point high data-rate communication which provides high bandwidth and operates in licens... | i | 4ff1acd1adf407e0298c2e9561d2439e |
In Ref. {{cite:904da66f248d5d5c6302c81d5ec9cb1f4ad5c713}}, Li et al. used a BEM numerical code for predicting
adhesion between rough elastic spheres. They found that a finite pull-off
force can be detected for higher and higher surface roughness as {{formula:fa6d35e7-685a-4d76-aa18-59d7354ea8f3}} is
increased. Fig. RE... | d | 5564bac891e61f4e681674e19c1e8158 |
A drift detector is an algorithm that can inform about any changes taking place within data stream distributions. The data labels or a classifier's performance (measured using any metric, such as accuracy) is required to detect a real concept drift {{cite:f9ac85824fc95e424148f4f160255b3a0568cc54}}. We have to realize t... | m | 242da6a18bd488ff713c36318a464a4e |
Although deterministic annealing approaches have been known for a while
{{cite:7418f79b91f4727a848a23179474d539c2b3c813}},
an online optimization method for such architectures is an important development,
similar to the introduction of a greedy online training algorithm for
a network of restricted Boltzmann machines
th... | i | faab99850c43587f8e8c5fb3a256bed4 |
Recently, feature aggregation based on self-attention has been popularized in computer vision tasks, on both images {{cite:9f79f2b64f2422b7f278fe928c8db4b444faec1d}}, {{cite:9f539669ffbe2e8e6e820ae9a7e508bd86f40767}} and point clouds {{cite:3b9c8b3600353776985d8cd59e366dc6f56bcc90}}. These attention mechanisms, called ... | d | dfd8dd8f990ccdc99737d87ee2676034 |
Figures REF and REF show results for randomly generated contextual bandit problems of two different sizes. Firstly, in the single-task setting, the relationship between the algorithm that has the true state abstraction computed a priori vs. the algorithm that does not pursue any abstraction at all reaffirms existing ... | d | f19efb150988c1ed04c60b719c1e06d2 |
The proposed unified conditional disentanglement framework yielded better segmentation performance than the baseline model Pix2Pix {{cite:863ae26ff3c313a1355f0be6bcc658e11de8399a}} and TCMGAN {{cite:be30271269c40a9676ea86c8954b55a57c62107c}}. In addition, the DICE score of our conditional disentanglement framework was ... | r | 613e5c900a26761942aa82978368390f |
We will first prove item (REF ). Since the constant {{formula:a56cd708-8b9e-465d-92a4-efc2b254043a}} in the statement depends on the complexity {{formula:9ca50256-f9c1-42e3-9f88-2a2dc2a15c09}} of the thin set {{formula:b8eafea6-a911-4f6c-89f4-9d03cece1884}} , we may assume that {{formula:f36f4e1d-43fd-4eee-b55d-30741... | m | 19866ed7cce1f45824ac59b345d426f0 |
Therefore, we propose the Multi-level Attention Fusion network (MAFnet) to fuse dynamically visual and audio information for event recognition. This network dynamically associates a score to each modality and time window in videos. The score highlights a modality at a given time window that may be effective to recogniz... | i | 1d3d9f893458eb8d8c3f0c889acccc50 |
Our DMRG results suggest that the itinerant electrons in the rare-earth {{formula:39291b12-bedb-4585-95d3-186be874670e}} orbital play a vital role in leading the ground state of the two-band Hubbard model to behave distinctly from the single-band Hubbard model at half-filling. Surprisingly, we have seen nearly “half-f... | d | d15c1c8422b958ee561ab2b22127d2bb |
The mass-loss rate we derive is comparable to previous estimates, ranging from {{formula:c6b0291d-066c-4bb6-aa47-9d10917d3919}} to {{formula:bb1abd7a-1ee0-4ff2-97be-c46d4020668f}} {{cite:cc4811682e5c0f1afa75577b1a97ecc48b3f0a98}}, {{cite:3b24c31267028e20f692080e6601b71fd0bbe6cf}}, {{cite:ad94f9bf23211fb7b6b32825159b1... | d | ee3808668ef360c2fb2cbfe991496312 |
In this section we corroborate our theoretical findings by showing some numerical results derived for the one dimensional dissipative XYZ model in the presence of a uniform magnetic field. As we discussed later, such lattice model belongs to the same class of systems addressed in Refs. {{cite:3d200e91905a2bf23004866469... | r | cac3748c29553dd97952049c78b6c99d |
Regardless of the large-scale nonlinearity parameter, the emerging tearing-mediated range is consistent with the predicted {{formula:b3f34153-27dc-4c83-b5e8-d311137cce77}} spectrum and a scale-dependent (mis)alignment of the fluctuations following something close to {{formula:f2b317df-d692-4476-a975-848aeae49ee6}} {{... | d | f8376f3a3e163b152ea7205e5f9af5cf |
In this section, a room geometry estimation method is proposed, which can be performed under enclosure rooms with the shape of a convex polyhedron. This work is conducted based on the assumption that the impinging waves are reflected from the boundaries in a specular fashion, which is justified for most room boundaries... | m | 491441852c8f5e09432836eb0ba66072 |
A decisive technical merit of all of the existing
QH quantum models is that
their correct
physical Hilbert space {{formula:1cf93b4a-427e-4880-9805-1ca1afe8ca11}}
is so easily represented in another,
extremely user-friendly
Hilbert space
{{formula:03e0432a-b8d1-40ee-bd15-f643f5190389}} .
After the mere amendment
{{form... | d | 2f8eb9b0372f3ab9be14624261599a3c |
BERT model is a multi-layer bidirectional transformer encoder Architecture that completely changed the previous methodologies of pre-training generated word vectors and downstream NLP tasks. The BERT model can take both a single sentence and a pair of sentences as input parameters {{cite:9fd72da0c9b5652f915d502405c4ed2... | m | 23dbeb96bf71bc3b1489ccab416ab55f |
The Bayesian approach is argued to be the only rational way to infer the value of an unknown property. Yet, the success of Bayesian inference relies of an adequate choice of the prior. If an unjustified prior is used, only because there are no evident reasons to choose a specific prior, the result of the inference is n... | d | 0c0c49b6928599a24b10a494bd48c804 |
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