text stringlengths 54 548k | label stringclasses 4
values | id_ stringlengths 32 32 |
|---|---|---|
We have investigated the gravitational lensing by the Bronnikov-Kim wormhole under the weak-field approximation
and in the strong deflection limit. the Bronnikov-Kim wormhole metric is the same as
the one of a wormhole filled with massless and neutral fermions in Einstein-Dirac-Maxwell theory in an simple case {{cite:c... | d | f9e9ebf48fbca769e6953cf080e5f3f6 |
This paper explores how representations learnt for object detection change with various privacy-preserving augmentations of the training dataset. We augment the COCO dataset {{cite:324378e02461a44707c8acccac135d58c2715847}} by face-blurring and face-swapping using an adaptation of StarGAN {{cite:595087573b5340d8d698eec... | m | 4a7adaca0dc1a0e16f07a29944e7992f |
The strong solutions of steady compressible Navier-Stokes equations with homogeneous
boundary condition has been studied in
{{cite:c4ca4c52e6aecf5b9967c549dd621660a1782a33}}, {{cite:027714e97550777e4040b8b2f5f24756bfdbc74b}}, {{cite:3dc6c8a443536186d7b9265cc1872b8b31f901b4}}, {{cite:8c459dc7ab87364350681d5dec7d1c785b92... | i | f865e048d72b752b902806606c1836fd |
Much of the interest in (milli-)lensing flux anomalies arises because
they may be caused by the elusive substructure generically predicted by
the hierarchical structure formation in the cold dark matter (CDM) cosmology
(e.g. {{cite:7079210d77d1ad11cf523142cfa2ae1e20489efb}}, {{cite:de786d1258da55bf62452141acbad19daeb6d... | i | 3919b362b2971c62cc5afedb02bc6139 |
The results obtained in this paper on phases and amplitudes of SSA components of NHSI and SHSI allow one to prefer Laplace’s formulation. This formulation allows one to understand the presence of the harmonic series (1, 1/2 , 1/3, 1/4, 1/5, 1/6, 1/7, 1/8 yr) in Figure REF . In a schematic way, variations in sea-ice ext... | d | 7bcf76ef163458c447b325ecf74579fe |
We categorised projects into treatment and control groups based on whether they were successfully funded or not, then estimated the effect of each crowd feature on fundraising outcome (i.e. fully funded or not), while controlling for project features. We do so using the traditional CEM measure of Sample Average Treatme... | m | df8a0a6950c962162d443bbc06fe1fe9 |
Finally, it must be emphasized that {{cite:16a895e9c05e3006be5d76468b11e5ebb76ccf1f}} was intended as a demonstration; the results presented here should not be considered as a verification of the Boström/Sernelius theory {{cite:b20003d4906c8d7f1c6a023756f75fb752520fbf}}, or as evidence against the Plasma model, but the... | d | e74009a24d1d3b59d76fb81fd664985a |
The idea that {{formula:0615ab7e-9aab-4934-a7f2-9b177a630b1c}} (the Newtonian gravitational coupling)
has probably experienced diverse values during the cosmic
evolution has many motivations. It began with Dirac's proposal {{cite:aba48b799f53fd71ebe0d1cc38d2e94eeaf76371}}, {{cite:cd987770ceb42a895b8f9c56efeae9e787190b... | i | 598645accc25115e58e4f9bb984dfe9c |
The spin-orbit coupling (SOC) in the presence of electric field can control electron spin and it can resolve the
designing issues of the devices arises due to the inclusion of local magnetic field.
Many fascinating phenomena, including spin-momentum locking, spin-orbit torque, topologically non-trivial spin textures ar... | i | e25fbf55473ada8601b088880cf8f654 |
Here {{formula:bf91c790-c2f2-4a14-a87b-6f70a12ef195}} is the Gamma function. When the graph size goes to infinity, the probability that a new vertex forms a self-loop tends to zero and thus it easy to check that (REF ) and (REF ) hold still for our model without self-loops following the proof proposed in {{cite:647c6c... | r | 7058d2e9d18c142445e7e1b925aa082a |
Our setup can easily accommodate a massless physical particle described by some Effective Field Theory (EFT) at low energies.
This would have several interesting applications. The simplest one is for particle {{formula:8ddaa4f5-e991-4f8e-a8c3-85947c306919}} to be a Goldstone boson of spontaneous symmetry breaking. For... | d | d74e546130a40c98bb25fa3c95e846ec |
Krylov subspace methods are often applied to compute the spectrum of {{formula:770c0ef9-55e8-4694-a28d-700db8d8a6fc}} , {{formula:be4ffbd4-afb3-4686-bffa-c2f74f39c8a1}} , or {{formula:a4aea7ee-13f5-4a2b-b1e5-834f245facaf}} for a given large and sparse {{formula:2126ff00-0ded-4080-b13b-886589ff9ad4}} matrix {{formula:... | m | f7bad71f4e9bb62b1dbb3761cf1f98c2 |
As shown in the first row of Fig. REF , baseline methods fail to preserve the striped pattern after warping, especially around the highly non-rigid body parts like the forearm and waist. The second row shows the results with the side view where baseline methods are not able to deal with large deformation in poses and l... | r | 583fc789a9d2b6626f2fd7c365ed6eb8 |
Fairness notions “without commons”.
In Section we further explore “without commons” fairness, since its connection to EFX for chores seems to indicate it is the “right” notion to study for copies, and since disregarding common items is a natural way to limit envy among agents. We define similar notions to {{formula:7b... | r | 9382c5ea964c55bb7e6251f1c018ba29 |
We have shown that MURD yields superior performance over DRIT++{{cite:1d0ed29b40c1ff20215792689154e1825c8a9fc9}} and StarGAN-v2{{cite:6ab0a3b03a6d90ad7b50ba32395573f3d06b9806}}.
For every pair of sites, DRIT++ embeds images in a site-invariant content space capturing information shared across sites and a site-specific ... | d | b52406cb914204d372b8bfd7d5e1d6ca |
State-of-the-art (SOTA) methods for image reconstruction tasks such as
super-resolution, MRI reconstruction, or inpainting, leverage the power of deep neural networks
(DNNs) to directly learn a map from the measurements to the corresponding
reconstructed signal {{cite:46c46bf0cb1e5f10f150ecb5c4f50a2b7ae27b73}}, {{cite:... | i | 55fa9e3cd9133666c87e89db2f3ae972 |
The first difference is that expression given by unitarity cut method is written using the spinor formalism, while results in this paper use the traditional Lorentz invariant contractions.
The second difference is that in unitarity cut method, we have assumed the
external momenta to be in pure {{formula:418f3ab6-d4a5... | d | 2f68355cf7e418eb33d0b6a35fe6aa5a |
The models specified here differ from previous Bayesian brain models in a few ways.
First, this study did not involve hidden layers or the learning of of any generative models.
For many, generative variational models that learn to represent unobserved “causes” are the focal point of the Bayesian brain hypothesis {{cite... | d | 9a68e248e28afca5778fb0ad7f5e454c |
We now discuss the choice of tuning parameters and various algorithmic considerations.
In the above description, the choice of {{formula:432314a9-0fa0-46f3-8622-d5437b90825d}} could be level-dependent but optimizing
these tuning parameters is outside the scope of this work.
Following the discussion in {{cite:4e6636655... | m | 3695fd8dccac765eb8b49112b9b9e5e8 |
First, we study the effect of several options for the proposed pipeline: (1) beat or downbeat alignment for input audio; (2) distance metric for the learned features; (3) miner and loss for metric learning. For (3), we use the proposed MultiSimilarity approach and TripletMargin miner and loss {{cite:f446c9829f155193fe8... | d | 9b73692d0381d37710b2d61ad926b2de |
The overall framework is summarized in Fig. REF .
Given an image, we first learn to predict part masks using MaskRCNN {{cite:1d8525079a7c0f5d4543318aa2bdbddf60ad26df}}, a well-established object instance segmentation approach (Sec REF ). In Sec REF and Sec REF , we introduce how to predict the direction and size of th... | m | de37397d5e0727116db9a5f38eb9296d |
with {{formula:83360d08-bf73-446e-978c-904d5862a34b}} {{cite:c2e8f1fbe0bed7e9d769aeb61ecc56ab45c7aa51}}. Having a non-trivial Lifshitz scaling exponent seems to play an important role in the phenomenology of cuprates {{cite:dee07792615010ecbeb98ba88153a35d5d544553}}. Its holographic incarnation is manifested in the so... | i | 4e80a3e7e070c5451a320a5317564c7b |
About the study of compressible immiscible two-phase flow, most of the works focused on isentropic compressible problems.
Feireisl-Petzeltov{{formula:9be74e85-1772-4b25-b319-b56d7de12c03}} -Rocca-Schimperna {{cite:abf8c2b8c45ec5f9214ff733664dbef67a9ba1e1}} established the global existence of finite energy weak solution... | i | 75766cb6997e3c83c7e73a2b1181a311 |
Software developers spend about 19% of their development time in searching for relevant code snippets (
meaning:NTF . e.g catcode:NTF a e.g., e.g., API usage examples) on the web {{cite:956313bb0fdbf6b55ac26f9ddd16b2c482967a44}}. Although open source software repositories (
meaning:NTF . e.g catcode:NTF a e.g., e.g.... | i | cf1cf207e90ceda03dfbbe000f58dd96 |
We also conduct experiments on the real-world dataset Real-billiard {{cite:abaee0db442e47aa5a7b7194b6c26530ca3f1eef}} with our supplemented question-answer pairs.
Note that the billiard table is a chaotic system, and highly accurate long-term prediction is intractable.
Fig. REF shows an example of the ground truth vid... | r | 2e8c184305ff1aed69a5aa05c35e2126 |
In order to overcome the complexity of rational decision making, an alternative approach has been developed. The underling assumption of the alternative approach is that individuals follow a particular heuristics when revising their opinion. The most prominent such approach is the one proposed by DeGroot {{cite:13f86fe... | i | 8b86c03f7c43f07f31097872ee9a3c0c |
Transbins:
Adabins {{cite:60d84fb35a171e7f26862665330b999b02c5cccb}} predicts adaptive bins and attentual maps, and fuse the later with the feature map from decoder {{formula:7fe13998-69ec-4487-b2b2-a6f496b42d62}} . The motivation is to fuse global information in the attenual maps with the decoder features. We take adv... | m | aeca786c0b50cb62f1d685ab55dec27a |
It is increasingly common in the natural and social sciences to amass large quantities of geo-referenced data. Researchers seek to use these data to understand phenomena and make predictions via interpretable models that quantify uncertainty taking into account the spatial and temporal dimensions. Gaussian processes (G... | i | 43cca88602d1a1e5dd5f358039ce56a5 |
We perform DFT calculations using projector-augmented-wave (PAW)
method{{cite:5260f77ab5bf35f1d95b1fc1bdf98f867fde0242}}, {{cite:12d1b2ca0a2dd02bbe6c9b6649334ea98eab9acd}},
Perdew-Burke-Ernzerhof (PBE){{cite:6575812e59798ce1b76c43711482bcc14396c3e9}} and
hybrid exchange-correlation HSE06
functional{{cite:ddd873994bbecf... | m | 6c9cd6d68800040f9d1119473bd71dcd |
A cell-free massive MIMO system is considered with 15 APs ({{formula:583b3710-22fa-4d9f-b860-7b46c627ade7}} ) and 6 users ({{formula:45f4291b-a2f0-4a35-91db-bec8769705f6}} ) who are randomly distributed over the coverage area of size {{formula:3ead7705-527c-4ea9-bc46-f7bb3ed62859}} km. Moreover, each AP is equipped wi... | r | b532ac6ad2f5668aa3d739c01672a22a |
Our work complements previous extensive mathematical literature on localized deformations in a variety of non-equilibrium settings {{cite:13be7e931071da3080d1d08921fe2e33031623bb}}, {{cite:51cea4c0891221a0f0e6ed8532d0ceb64614f352}}, {{cite:cf849c7f5e4ed7c68c569fb233c2ee6081e97b33}}, {{cite:c4ad64108fd31056c06dbdf45d7fa... | d | 1ad9c9e0aa0c5b6a958140589dc5d1e3 |
Current methods speed up the learning of radiance fields by different strategies {{cite:063a0f00ca8d4cda84b57cce842e79e52aeda0c7}}, {{cite:ec581c198c7a5c299b798cdd32dce92e892195c1}}, {{cite:a537229f4f677fd73258efb99c33d8af15e99e50}}, {{cite:af16d8f83335bb9d6792510238dbc138baa6a2d1}}, {{cite:1a8630172baa644ab7f67970f20a... | i | 0d8ab651458297bd136d9a41b8034e48 |
The computational complexity of self attention grows quadratically with respect to the image size. To achieve computational efficiency, we leverage the advantages of CNNs and transformer and adopt the swin-transformer block {{cite:213cee50feb64ba839f89610614774ea5b86e1cd}} in our framework. The swin-transformer layer c... | m | 39d769d2a1b245cdf1d1333435d49827 |
ViTranZFAS: This is our final proposed framework. Essentially, we take the pre-trained vision transformer model {{cite:2ee97fc7a00e24c2f7123c9dce0befdda5608835}} and remove the final classification head. A new fully connected layer is added on top of the embedding followed by a sigmoid layer. The network is then traine... | m | c4c18d6be403bc52bc268890cc5c1445 |
Triggered by the development of automation and sensor technology, unmanned aerial vehicles (UAVs) have become increasingly prevalent in military, public and civil applications, such as autonomous combat, target detection, video surveillance, data collection, disaster management, network coverage extension and so on {{c... | i | 0494a32ca6897d426fabd758df967e7b |
To illustrate the model performance under this subcase, we follow an example of the quadratic cost function with linear perturbation in Section 5.2 in {{cite:f451d07da366cf4a617edd2d546bf68a61da1f83}}: {{formula:d66f42ce-0b5a-4b7c-8b5b-8f643c602279}} We let {{formula:2ffdf7c4-6410-454b-8e5a-88cc85d61248}} and the dec... | r | 9f5f2a394d38af18506db8becd749133 |
Recent advances in deep learning suggest a new way of thinking for solving POMDP problems. However, very little work leverages deep reinforcement learning in partially observable environments. Among this work, {{cite:a30537d82aa19e9d32dc56de608582285f49db73}} adopted DQNs to solve conventional POMDP problems. A policy... | i | 5ecbd0e793a3b4d68a5dbf55ba2c84c6 |
In the strong deflection limit,
the logarithmic behavior appears in the deflection angle of light
in the Schwarzschild spacetime
{{cite:d28f0727a0d480d3a951e579997209d030946c71}}, {{cite:e45c6d00b676357f24c578e7c33163b401c36540}}.
Later, Tsukamoto showed that such a logarithmic behavior is
a rather general feature in a... | i | 5237401fe7418ca6369822bfa365415b |
For systems where there is a sign problem {{cite:c7d7b00cdd739f4d04e61eef11bd65377a496146}}, constraining the random walks in sampling the space of auxiliary fields, will led to considerable progress, these methods are called constrained-path Monte Carlo (CPMC) {{cite:ab998d58dcf025582280677463cea21622d80fc4}}, {{cite:... | m | efd753820e3dac319a5934b0fee28faa |
In order to understand why the inclusion of resonances above threshold lead to an improved determination of the {{formula:f86e07ca-413f-4589-9a8a-56df065c2975}} quark mass,
we provide in Fig. REF a graphical account of the landscape of {{formula:e36ed12c-63dc-491e-8e68-8a79fef067f0}} above threshold.
The upper plot ... | r | 3cf8bdd888f2b69351a6a271993ed84d |
Inference for the MSCE model is straightforward using the adaptive MCMC algorithm of {{cite:43fa0837e0cdce206f0bd4be062b7561b2bad5b0}}, and convergence of MCMC chains is relatively rapid; in practice, 10000 MCMC iterations is more than sufficient. We believe that the MSCE methodology is an interesting extension to the ... | d | 23c3da00d701c8c8a6116f82ea78eb4c |
Uncertainty for ADL. ADL can use uncertainty to select samples, but it does not mean it can totally avoid uncertainty in training process.
For most of shallow models such as SVM, Logistic Regression etc., their uncertainty is not so obvious in training. However, the uncertainty of ADL is very obvious as it is based on ... | d | 01b70f6ad0511e6ae81433f5affcbf40 |
The charges of the {{formula:cd101441-cd36-45c5-9373-ba8fd0a306b5}} field are also such that a global PQ
symmetry will accidentally emerge from this local {{formula:d56db85d-6ea7-44e9-ae39-da9acf2abd56}} . Moreover
the global {{formula:2377ef91-5f0f-4653-a983-8e4abe1ad4b1}} symmetry has a color anomaly due to the
pre... | i | 15978c1375b3b388f1637cee2deaa1b7 |
We also compare our method with KL matching {{cite:d58191395fe2f4eb2a8051538f92616c18d11e74}}, a competitive baseline evaluated on large-scale image classification. MOS reduces FPR95 by 14.33% compared to KL matching. Note that for each input, KL matching needs to calculate its KL divergence to all class centers.
There... | m | 1e35141c2abb2dca1daa41938ea372e1 |
The underlying idea behind this approach is self-expressiveness, which posits that data points sampled from a union of affine subspaces can be accurately reconstructed by a sparse linear combination of other data points in that subspace. The process of computing these linear combinations is known as sparse self-represe... | m | 99410565bc1ed32eea1714669d7745ef |
When C.1 holds, the approximation error induced by MOD factorization is negligible, since the original MOD {{formula:ce009fa8-9b8f-480f-901e-44569adadad8}} can be reconstructed exactly using {{formula:855245c1-c6ec-4b8c-ac89-4455a8df2083}} by applying the convolution formula {{cite:2b40c0ef75c9cf9ea41329ed3d758660e05... | m | b358a6b11e3c067eed08705e58b4ebf1 |
In a number of CL settings the observed accuracy can be a misleading metric for studying forgetting, particularly when compared to finetuning approaches
Naive training with SupCon {{cite:85293604e9578a49547f5a2814ba64dcb828b294}} or SimCLR (in the unsupervised case) have advantageous properties for continual learning... | i | 10fa5ab8b722aeaa1f253e9dbbf77e1e |
There are a variety of literature on distributed training methodologies such as data parallel {{cite:8df8e5577ae7c2109d99e0bac2b11417994d20b4}}, {{cite:c43ab76ce7d80328b935aa5a29e3ec9bb7f619bc}}, {{cite:3a88cf9bb1b4ede47ad60d5f64e9566128a16460}}, model parallel, pipeline parallel {{cite:30f1e4487241d330bdbc8443a217c27c... | i | 1e92f034912f648a1dd19ff1d8d5970c |
On the unsupervised side, {{cite:410a83449cdfc7f6e15f9bdd78c977abbb1f30bf}}
experimented with models that include losses corresponding to the
three criteria, and that could be used both for model tuning
and selection. Among such losses, many of which had been already
explored {{cite:a96d56178d62a4651bfeb73ac2cf10a94b5f... | m | 1887bd0796fd1b42566e66efb052c6a3 |
By part (a) of Lemma REF , {{formula:378a3974-4040-4124-afcb-2a85d5d66b42}} can be implemented by a ReLU network {{formula:94f4c66a-207a-4330-ae9b-a9a401eb4d71}} with width {{formula:e715dd89-0da5-4649-a1bc-00c69105feea}} , depth {{formula:24f71d7d-592d-4ba6-80e8-08eee5c78523}} , size {{formula:a166dfef-0f08-4059-8fc... | r | 4a2c500245763b387ae86e49f2399616 |
Proposition 2.3 ({{cite:d7a38e0a3cc4e0465b95241d1a56683a76ff4ac4}}, {{cite:814da7a17750f85be76d9b9f7694a6985294d1a0}})
Let {{formula:45fafb2b-f102-46aa-ac7d-10acc82e2ffa}} . Assume that the initial data {{formula:2e78c547-1168-429e-bbd1-af48c606721b}} {{formula:77fbb8a5-408f-49df-9ef0-23a34db045e2}} satisfy
{{formul... | r | a8096ab5fcb64c61ccbd60d611948f2b |
An alternative method to achieve a sparse classifier is to use a sparse prior distribution on the model parameters and update the classification model from Bayesian perspective. In fact, the {{formula:320708fc-f3e9-4dd5-a5cd-10b652ca1b35}} -regularization is equivalent to employing a Laplacian prior distribution {{cite... | i | 97764e7346ffbb58da2da32f8bfc2d0b |
As mentioned above, the choice of the library in rvm is important for the performance of MEDIDA. Building an exhaustive library of the training vectors and inclusion of any arbitrary nonlinearity and function is straightforward but becomes computationally intractable quickly. Any a priori knowledge of the system, such ... | d | 519dc22487747e91c1af8acbf670761d |
In this section, we numerically justify the efficiency of Transformer-MGK/MLK and empirically study the advantage of using mixture of keys on various benchmarks, including different tasks in the Long Range Arena (LRA) {{cite:ec8981527d4561f0a8c7ec391b20b5b40b5901de}} (Section REF ) and language modeling on Wikitext-103... | r | baa109180391dd67cb8aeffc500badd6 |
Note that it is impossible to decide OV in time {{formula:0c3fa1e7-c784-4c23-afd7-9627a93a8d9e}} , so when {{formula:40ff5985-7bef-4e2e-bc09-0c8067e50651}} is polylogarithmic (as is the usual assumption), our algorithm has only polylogarithmic overhead over decision. Thus our result is able to turn the {{formula:aeab0... | r | e03bf431a56843753ad8b22ec614aae8 |
As a reasonable and efficient characterization for dimensionality reduction and pattern recognition, the low-rankness has been witnessed and well explored for matrix data arising from a wide range of application problems. The resulting matrix optimization with embedded low rank matrix structures can be found in diverse... | i | 418b872c4bdf0a749905968be51ba0db |
We evaluate our model against all the published approaches which made their code publicly available: Social Force model (SF) {{cite:8edd7885375ac8b04e0c423325e247d29227987b}}, Linear Trajectory Avoidance (LTA) {{cite:e3aa9dcae312e0a5c58936c776bbf232243bfb04}}, Vanilla LSTM and Social LSTM (S-LSTM) {{cite:4152881b9c629... | r | 7fc92ab715e06e9e841321f9e5a13d8d |
First we must choose a global and static reference, since the
Neumann solution consists of integrals defined over the entire
radiative domain. Such reference obviously exists, in which the
velocity field of the fluid flow is also appropriately defined on a
grid. Next our scheme requires the mathematical expressions for... | d | bbd73cd951ac4193ab96fe51ca14694c |
First, we infer the interacting-particle systems approximating the dPMF dynamics by modifying the systems known to approximate cMF dynamics {{cite:47a3eed62bdfc74261783b9f922b7e478982d48d}}, {{cite:c542bee5f85bf112d87539d17fc5474ac26a2ff8}}.
This involves considering noisy synaptic interactions, whereby spiking updates... | m | 17dfe6a855dc3a2fd388960225a2dc21 |
We qualitatively and quantitatively compare the sinogram results of our DP loss with the original VGG16 perceptual loss {{cite:09fedcddec155793e1a81aaf8db69ecf929e0e9c}} trained with a SIN model. The SIN model learns 1D super-resolution from a 23-angle sparse-view sinogram to a 180-angle full-view sinogram. The models ... | r | 670c699569c6ce17729c59085e552210 |
In this section we describe the methodology of analysis of JLA data to obtain
bounds on equation of state parameter {{formula:24929243-41ea-4276-b028-6c29e8d88c94}} of dark energy.
There exist diverse statistical techniques for analysis
of JLA data. Some of these methods are discussed in detail in
({{cite:40b858a348d2... | m | b3d1154ff34dc8ce5093bb3566dfd410 |
In the swampland program (see {{cite:623fee0919ac2d42209f48d7041041b132fa1888}}, {{cite:575ba2700fbb584f736a9a0d8f54ad7f7ddaa6aa}} for reviews), the absence of
global symmetries in quantum gravity (QG) plays a central
role. A recent incarnation of this is the so-called cobordism
conjecture {{cite:1e557b9d129142269dcba7... | i | 7acfd82263af1f9f6bb4773ca0d854bd |
We focus on the case where {{formula:5e6a3ee6-15fc-4243-b198-67cca0de8e72}} . While the entrywise eigenvector analysis method of {{cite:a72ce7cd3be9cd275267e53ece351283a72ff74d}} allows us to handle slightly sublinear {{formula:1e953d2c-83ee-4b61-a12e-5e5772db1851}} , it does not allow us to match existing results for... | d | ffae2d20525cab6b978d8c6612b0bf4c |
At first glance, two algorithmic ideas seem relevant for tackling the challenge of computing approximate pure Nash equilibria. The first one is to follow a sequence of deviations by players who improve their utility by a factor of more than {{formula:0b9ad585-c62b-490a-bd86-dcb9a8888829}} . The existence of a potential... | i | 78070a36bfee5477c0cc510d25dddd42 |
A powerful tool to analyze the strong coupling behavior of {{formula:7fbb7588-21f3-4472-a6c4-015cc6dde731}} {{formula:f312f3ac-7447-4766-8f7b-5749e35ea83f}} gauge theories is given by Hanany-Witten branes setups {{cite:a67c5b63408a1b55853cc8ccf68a02f0bd77fe3c}}, which in this case involve webs of 5-branes, a.k.a. pq-... | i | d9944748900c7ba25624ea1eea5db54a |
{{cite:b197b1912f55644e8ee54a8e84fcc50433d32f17}} have used red clump giants drawn from a wide range of Galactic longitudes sampling the outer disc to find a broadly flat longitude-averaged rotation law within R{{formula:9e8d8d32-9fb2-469f-b7ea-0c6d4347fe37}} kpc, with typical circular speed V{{formula:f43c97da-2b39-4... | r | 0e7e253958f38b7753d7a909339754dc |
To be more specific, given a class of objective functions {{formula:1c562f45-388b-4461-b9cc-2c3113fcf875}} , the aim is to determine the argument {{formula:11b70cc3-46c3-4c90-8f91-8e1b04e3a270}} that leads to the smallest objective value even for the worst-case function parametrized by {{formula:ed241b6d-87ac-4c99-bfe... | i | 9c266c63841efdbd6d04976a320c407a |
In this section, we apply the proposed composite EMPC to the stand-alone IES and compare its performance with hierarchical real-time optimization approach to demonstrate the effectiveness of the proposed method. The optimization problem is solved in Python based on CasADi using the BONMIN and IPOPT solvers {{cite:7b5a5... | r | cd2ca107adce172a6b262497e2be1fc7 |
{{formula:b6f0ba8e-338b-4972-9965-347c23e6d35d}} has been measured for the first time in 1992 by COBE {{cite:37386bbd7bd4aa3b23ecd9419d4b4238c1ef54ff}}, {{cite:b11e4f1f119536a5662ffb2e21461b1498f51eed}} from the 1–year maps, and in 1996 from the 4–year maps {{cite:b9fda1a668ce34aaf314c9425341f128d25faf24}}.
The COBE d... | i | 3b5b0bd8dac7821f589ad579db170958 |
In recent decades the performance of automatic speech recognition (ASR) systems have been significantly improved with the successful application of deep learning techniques. In the conventional deep neural network-hidden Markov models (DNN-HMMs) based hybrid ASR systems {{cite:d617fea47b2b152cdf9a1193b2adfea2ecaf2bd6}}... | i | e171d227ea253f05a52d2b61cd57374a |
In this paper, we propose a novel holistic model, SuperGF, which unifies global and local features for visual localization. It works directly on the local features generated by the image-matching model and aggregates to a global image feature, similar to BoW {{cite:6682ef65a58182a7c3cd4054277d92075b4700ab}}, {{cite:ff6... | i | a3b40701f9aea2275def006cbebee2c7 |
EF1+PO. EF is actually a demanding fairness notion, in the sense that any approximation of EF is not compatible with PO.
Instead, initiated by {{cite:a9e13479d9479e24a03806b11ad635a0fa95a7a7}}, most research is focused on its relaxation, envy-freeness up to one item (EF1), which means the envy between two agents may ex... | r | 999446cbfc6bdec18dcfabbbbca9242f |
With the ROM basis at hand, the classical Galerkin ROM for a given dimension {{formula:f4efeb23-2615-4eeb-aedc-72b58bfa249d}} can be readily constructed and is given by (REF ) in Algorithm REF . Thanks to the discretely divergence-free condition assumed for the FEM, the pressure term {{formula:2fffffdc-dff3-4538-bfaf-... | m | fcbf6388e5e19bc64c6e21182fc24c36 |
The success of ReLU-based neural networks in recent years originates from their learnability and expressiveness.
Piecewise linearity helps them avoid gradient exploding or vanishing problems of early architectures and, in terms of expressive power, they are shown to be able to capture an exponential amount of variation... | i | 68773382dfca27492266f53e2f432d51 |
More recently, with the rise of deep learning, a number of methods relying on deep neural networks have been proposed to address the mass-mapping problem.
The strength of these approaches is that they provide a practical way to leverage simulations as a prior to solve the mass-mapping problem. In particular, the DeepMa... | i | 2af00195edc941fe56b7c2f870ce6157 |
Analysis and control of agent-based network systems have been an active
research topic in the past decades, and the consensus problems have been
extensively studied in the literature (see,
{{cite:a6f816501edca873f5e05122b3ac0de00e4d4c12}}, {{cite:93d342a8fd1fde5c6cf48488c8441995b1206441}}, {{cite:4ef3be0fd7b081bfd523b3... | i | cddd579d442e73d064918c150efbbc82 |
However, the recall of original GAN, WSMOTE, and EMICIL is much better than SMOTE, but worse in precision and FAM scores. It is worth to mention that, WSMOTE is better than EMICIL and EWSMOTE on precision, which means the decision boundary, is prone to the majority class region in order to generate the new samples. As ... | r | 817542731d0bb094ba31224e3920b8e3 |
Monte Carlo approximations {{cite:b86a95b50f1f582c37ce0beb99cdc792194b585e}} are based on the Law of
Large Numbers (LLN) in the sense that an integral like
{{formula:05af3213-3af8-4d6f-bd03-16fd1fcfb524}}
| m | 438eae59eeb1ec9763042f90e8625bf4 |
{{formula:ebcb8ca1-f32b-426a-897a-bf6931e56711}} designates the distance to the border of the nearest edges and {{formula:a529ccdb-7c5e-4be6-b2ce-548e5b6c22d1}} designates the distance to the border of the second nearest edges. LB score is shown as {{cite:cfd1a00d7c445c6611edeb28eb79dae0eaa88f7b}}. We use the deep co... | m | 9519c471845444a83f7cea42abf971fb |
However, this choice of tangent space is never fully justified in terms of the model under consideration. In {{cite:82ddb366eb366d55608fea98c297d3df1b41ed2c}}, the authors do justify the necessity of these restrictions by noting that if {{formula:94b74c98-7d30-43ef-9f39-90a76fcb0ef0}} and {{formula:b1d8e4a4-8266-4edf... | d | 932b0ec61878ca0925c210cf0d8ed3aa |
Calibrated equalized odds postprocessing is another method that changes output labels after classification to preserve fairness. Introduced by {{cite:a0ac4cbe2d4097ba532e73619dfe993d9e624b53}}, the method builds upon the work of {{cite:0fefc6335ba40b7b259d7cc78bb3d9e10032784c}} which introduced the equalized odds fairn... | m | 7ba29fa4465f8660416511c06c8d3c70 |
It is known that the HMC algorithm with exactly one leapfrog step
boils down to the MALA {{cite:bc25bbe553f6c113c53ce9882dcc9edf0217b25b}}. As mentioned
before, {{cite:673d2459baf287b8662c94a424af517fef3bba60}} establish geometric ergodicity of
HMC when the `mass matrix' in the `kinetic energy' is the identity
matrix {... | d | 91669ba320a80a864354e8c160f2a98a |
(1GMEdd t)2
=6.810-32 (M10 ng)2
(267 nm)-2
(d200 m)-4
(10 m)2(t20 sec)2.
After performing time Fourier transformation on the probability {{formula:0a05fe0f-674a-4f32-a71c-67b7e270b53a}}
obtained using the spectroscopy experiments, the least necessary
precision to detect the QG effect in our proposal is approximately... | d | dd0b43e34ad8ab701c06367ae2a4540b |
The presence of such a “topology” allows one to define a continuous mapping from a topological space to a topological classThe presence of a pseudometric makes it possible to determine the continuity of a mapping from a topological space in the standard way, using spherical neighborhoods generated by the pseudometric. ... | i | 0ce62c9e7bea86d2fbfa7f58735d5333 |
Perhaps the greatest utility of synthetic data exists in problems where real data is not available - problem spaces where data collection is prohibitively challenging, or where object and events occur rarely and spontaneously in the wild. How might we increase the performance of a model trained on purely synthetic imag... | d | 9700a2e5d7bb21190f870266c11f2244 |
The authors in {{cite:47fe1c3e8ccffad4d664d365755ab909ba9988d8}}, {{cite:7dd0d54039fd0ae8f43a0dab9cd17e43728c48f8}} enabled HE for FL, where the server is honest-but-curious. Before training, the server randomly selects a client as a leader. The leader generates and shares key pairs with the rest of the clients. The cl... | m | c19649bb16b5d75f3e798423767eb17f |
For SALICON {{cite:66481d2d7cd8a3ab20113df9657cc9f6b74e83c6}}, the additional results in Figure REF yet again confirm the benefits of exploiting objects' dissimilarity on saliency. We show results from scenes with multiple objects and from scenes that consist of a single object to demonstrate how dissimilarity affects... | r | 3935507d848f5b2aa2dafe68ede7948f |
In Appendix E of Runeson et al. {{cite:e8adbf7901273d078bd052207999fcb73c73cdef}}, there is an
example of a consent information letter. It informs the interviewee
about who the researchers are and how to contact them, and it
also highlights that participation is voluntary, the interviewee may
refuse to answer questions... | d | 89728e64ce36b52a64aed717849d5ccc |
Since the operator {{formula:698d0051-ca02-4e99-a84f-7b3beaf3bf35}} is self-adjoint, by using a weak formulation and a suitable variational framework, Servadei and Valdinoci {{cite:97c1b5f69726b92d8c62f343a5a51b86a1e3e6ef}} investigated in detail the discrete spectrum of {{formula:6c367f57-89d7-4602-a659-27bcc098dcf3}... | r | 49181158c4dba182c499a3f829cf5fd1 |
Note that our requirement on the sample size {{formula:6a8d164d-8bb2-44c6-b153-c3be2f598292}} matches the known regime for exact recovery with nuclear norm minimization {{cite:556a0069360c51dcd71894aaff5418d5b9510363}}, {{cite:480a767cf60965691e50718428ed1ba9570fe145}}.
Since we are interested in the high dimensional ... | r | ae575d947125ff4e6ffeed2426f27950 |
Much of the world’s information produced daily is stored in structured formats such as tables in databases and documents, or tables on the web. Question answering over these structured tables has been generally considered as a semantic parsing task in which a natural language question is translated to a logical form th... | i | eed1d1d4df48b965b0a7a01be6b0fe6d |
Recall from Lemma 2 in {{cite:831b9fcad75bf233a7456a827f0ef54e51c30291}} that the process {{formula:814a1463-5e62-44dd-98ac-c6646f9236ec}} is exponentially {{formula:fa2960c2-60fd-4be5-abaf-b206b0437ef9}} -mixing, which implies that {{formula:7517c645-ec60-4227-93e5-d8440b0fcd49}} , where {{formula:3d7d968b-b872-4c8e-... | r | fadabb77c5f32bc71ed570b936936962 |
The extension of a quadtree to {{formula:87dcd279-f152-4d0d-94bc-29c213bbff26}} leads to an exponential dependence on {{formula:7faa3aaa-6697-4285-b462-1d57ad91a39d}} , because the {{formula:9bb63241-c164-4959-9560-aa52a0e87c0b}} -dimensional box is subdivided into {{formula:b9c5109a-af0f-43ff-8dc6-858659235934}} sma... | r | 221295316ffb218c23fccb921f0a42c7 |
In {{cite:b8d635d9fba7037b732bd955db309f3a2160662c}}, the privacy-independent leading term has a dependence on {{formula:92335bae-32c3-42c0-a17e-82cff84b5740}} rather than {{formula:2cef4bb7-0a1c-4b9c-922d-afa6198497e1}} in our result (i.e., the first term in (REF )). This is because they directly bound the transiti... | d | 15f247d5efddf000e84267631c8e8a65 |
{{formula:2d24139e-8f34-4260-96fd-0fec60312d0b}} , {{formula:9cbaead7-4fd8-4d89-a5fa-c3b7dd1323f1}} , and {{formula:ba553acc-42ce-4439-9d48-8e99d8f469c1}} always agree at {{formula:36424238-ab9e-4442-abf1-1473978a8705}} [Figure REF (a)], since our protocol is exact in this case. The OTOC stays nearly constant at {{fo... | r | c26e6b394c73d37bda5a9fef14c97a45 |
Besides those results, an important problem in random matrix theory is the asymptotic behaviour of the least eigenvalue of covariance matrices, when the matrices' dimensions are equal. In the case that the entries of the matrices are normally distributed, the limiting distribution has been described in Theorem 4.2 of {... | i | 28ee75ebf0188ef29c9b7a3ba59d905f |
Another bottleneck in the previous parallel algorithm of {{cite:84d0614f0f89f24a340c6af66ba3784af5910bb7}} is solving the so-called two-respecting cut problem, where the randomized algorithm of {{cite:84d0614f0f89f24a340c6af66ba3784af5910bb7}} requires {{formula:aa5d30a8-ac35-4c6c-b7e6-1eea4b18c5bf}} work and {{formul... | r | 01c72b5c3b11141fb3d2e4100cfd39ae |
Another noise assisted variant of MD includes ensemble EMD (EEMD) which leverages the dyadic filter bank property by adding Gaussian WN directly to the signal {{cite:d2704a171e06510850333b214da667e18ef45f9f}}. This procedure is repeatedly performed, and for each iteration a different realization of WN is used. The outp... | i | cab04b767d42e74234a529b05a151da1 |
UNet, initially proposed in {{cite:64727a450d8021bb6659c0570acea59b488aa87b}}, is mostly applied CNN structure for the WHS {{cite:76e341acd155e61dc136eb9a2cd1373f8767ddcd}}, {{cite:c186c7b9bfed8a6352e5c6d602aec44b122ff8bb}}, {{cite:5e37d53e4ac4b0b3cb08d808dd53f043131d8140}}, {{cite:b0c4d65f21a24f20e8c4e08783cb0995ee3ae... | m | 1cc7a9d9c0cc69b094204f21fae954d5 |
Is the learned compression function suitable for learning a hierarchy?
Does the learned hierarchy transfer across different tasks in the same environment?
How does our HRL algorithm compare against state-of-the-art flat algorithms such as Self Imitation Learning {{cite:c9504938615cbc51403105e0ef57f05eae4a8d74}}?
| r | dc7c84be6620f04a2d8e1becdfac60c3 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.