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**A**: [58] decouple the KLD into two uncorrelated losses and combine them by weighted summation.**B**: [19] use Kullback-Leibler Divergence (KLD) between the softened logits of teacher and student models as the loss to align the output distribution, and Zhao et al**C**: Response-based KD methods [19, 58, 3] have the n... | CBA | ACB | ABC | CAB | Selection 1 |
**A**:
The proof can be found in Appendix A**B**: More results on aliasing for composition with smooth functions can be found in [Ber+06]**C**: The aliasing error is quite substantial, but since all energy in the theorem above is confined in highest possible harmonics, in practice one can expect to have milder discrep... | CAB | BCA | CAB | ABC | Selection 4 |
**A**: Suppose that teacher and student are the 3-layers and 2-layers convnets with kernel size 3×3333\times 33 × 3 and stride 1×1111\times 11 × 1**B**:
Figure 1: Illustration of semantic mismatch**C**: (a) shows the receptive field of the middle pixel of the final feature map, where the blue box represents the teache... | BCA | BAC | ACB | ABC | Selection 2 |
**A**: Combining subspace clustering techniques with ENS-t-SNE seems like a promising idea**B**: Second, ENS-t-SNE offers a powerful tool to perform comparison tasks on interesting subspaces, something that is typically done with small multiple plots (which do not support the full range of comparison tasks) [16].
We il... | ABC | ABC | ACB | BAC | Selection 3 |
**A**: Instead, it is necessary to obtain a low-dimensional embedding of the history, which assembles the low-dimensional features across multiple steps (Hefny et al., 2015; Sun et al., 2016). In practice, learning such features and embeddings requires various heuristics, e.g., recurrent neural network architectures an... | BAC | CBA | BAC | CAB | Selection 2 |
**A**: (2007); Munos and Szepesvári (2008a); Chen and Jiang (2019) and the references therein.**B**: Without any coverage assumption on the offline data, the number of data needed to find a near-optimal policy can be exponentially large (Buckman et al., 2020; Zanette, 2021).
To circumvent this problem, a few existing w... | ACB | CAB | CBA | ABC | Selection 2 |
**A**:
The asymptotics of second-order Newton’s methods for unconstrained problems have recently been investigated**B**: Bercu2020Efficient designed an online Newton’s method for logistic regression, and Boyer2023asymptotic generalized that method to general regression problems**C**: Compared to first-order methods th... | ABC | ACB | BCA | CAB | Selection 1 |
**A**:
The present paper suffers from the same rather severe restrictions on hexahedral meshes in 3D as in previous work**B**: The analysis of discrete inf-sup conditions for general hexahedral meshes remains an open problem**C**: Another open problem is the analysis of isoparametric generalized Taylor-Hood families i... | ABC | BCA | CAB | BAC | Selection 1 |
**A**: WaveMix uses multi-level 2D-DWT for lossless and image-appropriate down-sampling and token-mixing, that model image priors, such as scale-invariance, shift-invariance, and edge-sparseness**B**:
We proposed a novel and versatile neural architectural framework – WaveMix – that can generalize at par with (and some... | CBA | BAC | ACB | CAB | Selection 2 |
**A**: This provides a total cost O(ln(s)sn)𝑂𝑠𝑠𝑛O(\ln(s)sn)italic_O ( roman_ln ( italic_s ) italic_s italic_n ).**B**: The detection of columns in B𝐵Bitalic_B at each step can be made
with cost O(ln(s)n)𝑂𝑠𝑛O(\ln(s)n)italic_O ( roman_ln ( italic_s ) italic_n )**C**: O(bin)𝑂subscript𝑏𝑖𝑛O(b_{i}n)itali... | BAC | CBA | ABC | ABC | Selection 2 |
**A**: There are two major bottlenecks irving2016deepmath formal methods must overcome: (1) translating informal mathematical text into formal language (autoformalisation), and (2) a lack of strong automated reasoning methods to fill in the gaps in already formalised human-written proofs.
Informal methods either tackle... | BAC | BCA | ACB | ABC | Selection 2 |
**A**: species) with the same block membership play the same social/ecological role in its system (Boorman and White,, 1976; Luczkovich et al.,, 2003). In food webs, species playing the same ecological role are said to be ecologically equivalent (see Cirtwill et al.,, 2018, for a review of species role concepts in food... | CAB | BCA | ABC | BAC | Selection 2 |
**A**:
Figure 5: Performance of FactorNets for individual rotation learning**B**: (right) Distributions of absolute percentage errors (in %) of all data points in the dataset. **C**: (left) Predictions of rotation angle vs. the ground truth (normalized to [−1,1]11[-1,1][ - 1 , 1 ]) in test set | CBA | ABC | ACB | CBA | Selection 3 |
**A**: In this work, we investigated the limitation of a general self-supervised pretraining and finetuning approach on weakly-supervised tasks**B**: Our method achieved state-of-the-art performances on several PU learning and semi-supervised settings across vision and natural language processing and is particularly po... | ACB | CAB | BAC | CBA | Selection 1 |
**A**: Moreover, the usefulness of finding latent structure in the layers motivates the use of latent-space models as a noise-free smoothing of the observed network, as proposed by Fisher and Pinter-Wollman (2021)**B**: Understanding the layer dependencies in a multilayer network can inform the development of survey de... | BCA | BCA | BAC | CBA | Selection 3 |
**A**: Experiments below used the 11-qubit trapped ion quantum computer described by Johri et al**B**: johri2021nearest ,
and where necessary, the larger IonQ Aria machine with a capacity of 32 physical and 20 algorithmic qubits (ionq2022aria, )**C**: A crucial point to bear in mind with quantum computing is that the m... | CAB | BCA | BAC | ABC | Selection 4 |
**A**: Pei et al. (2020) firstly draw attention to the limitation of GNN on less-homophilic graphs.
Since then, various GNNs have been proposed to improve performance on these graphs. H2GCN (Zhu et al. 2020) show that proper utilization of ego-embedding, higher-order neighbourhoods, and intermediate embeddings can impr... | CBA | ACB | CBA | ABC | Selection 4 |
**A**: The dsolid lines correspond to the risk trajectory for the unstable balanced equilibrium at initialization**B**: Dotted and dashed lines illustrate risk trajectories under three different slight perturbations from the initialization.
In Figure (b), the left plot illustrates the reduction in total risk over time.... | BCA | CBA | CAB | BAC | Selection 1 |
**A**: The data set includes approximately 3.83.83.83.8 million data points and 50505050 attributes**B**: Using only attributes that are known before the labor, we generated two classifiers that attempt to predict the type of labor out of the five possible options (e.g., spontaneous, Cesarean): a decision tree classifi... | BAC | BCA | ACB | BAC | Selection 2 |
**A**:
The MK algorithm (Mueen et al., 2009) from Mueen et al**B**: However, it is outperformed by more recent methods in terms of runtime, in particular QUICK MOTIF (Li et al., 2015), STOMP (Zhu et al., 2016), SCRIMP (Zhu et al., 2018), and VALMOD (Linardi et al., 2018a).**C**: published in 2009 is likely the most wi... | CAB | BCA | BCA | ACB | Selection 4 |
**A**: Besides, we consider both additive and multiplicative communication noises in the process of the information exchange among nodes**B**: and mutually independent and it is required that the expectations of the regression matrices be known in [28]-[29].**C**: All these challenges make it difficult to analyze the c... | CAB | CBA | BCA | ACB | Selection 4 |
**A**: In Table 1, we report the matrices and their most significant properties**B**: The notation MM is used to refer to the Matrix Market Collection, and SS for the SuiteSparse Matrix Collection.
**C**: The sources used to retrieve the matrices are specified in Table 1 as well | ACB | BAC | CAB | ABC | Selection 1 |
**A**: Then, we proceed by presenting and discussing the experimental results
**B**: In this section, we present and discuss the experimental evaluation results**C**: First, we introduce the experimental setup used for the evaluation, including the dataset generation procedure, the evaluation metrics, and employed deep... | ACB | CBA | ABC | CAB | Selection 4 |
**A**: However, a standard cell does not capture the order of the interactions and this is the motivation for the necessity of extracting schedules. It should be noted that the same cell can be used to support more than a single sub-circuit**B**: For example, a tile can be used to read NISQ circuits as well as surface ... | BCA | BAC | ACB | ACB | Selection 1 |
**A**: For the second phase, we train the Param-Net on MRiLab dataset. The weights of the auto-encoder are frozen during this phase**B**: For both phases, we used Adam optimizer [20] and weight initialization as proposed by [21]. Mean squared error (MSE) loss was used for both phases.
**C**: The training process compri... | BAC | BCA | CBA | ABC | Selection 2 |
**A**:
We note that the numerical methods to solve generalized diffusions (4) can also be formulated in the Eulerian frame of reference based on the notion of Wasserstein gradient flow [35]**B**: In a recent study [33], the authors initially employ a fully connected neural network to approximate ρ𝜌\rhoitalic_ρ and su... | CBA | CBA | BAC | ACB | Selection 4 |
**A**:
In this text, we will freely make use of techniques from micro-local sheaf theory for which, we refer the reader to [16]**B**: Hence a reader only interested in the results may ignore them. Let M𝑀Mitalic_M be a smooth manifold.**C**: Nonetheless, micro-local techniques will mostly appears in proofs and not in ... | ABC | CAB | ACB | ABC | Selection 3 |
**A**:
We first examine the individual changes - arc addition, reversal or removal - which the HC algorithm makes at each iteration as it learns the DAG structure. In particular, we note where changes are arbitrary; that is, where two neighbouring DAGs are Markov equivalent. Figure 2 shows the proportion of graphical ... | ACB | ABC | BCA | BAC | Selection 2 |
**A**: First, we show that the Minimum Target Set Selection problem reduces to computing the distance of a divisor on an auxiliary undirected graph from a recurrent state (Section 3.1). Then we show that computing the distance of a divisor from a recurrent state reduces to computing the distance of a divisor on a sligh... | CBA | CAB | CBA | BCA | Selection 2 |
**A**: Moreover, it surpasses the capabilities of employing 2D convolutions alone by effectively obtaining a larger receptive field. In order to provide a deeper comprehension of the salient aspects of our proposed method, we present the following theoretical analysis concerning the specific region where the network pe... | CBA | ABC | CAB | ACB | Selection 1 |
**A**: Ω=(0,12)2Ωsuperscript0122\Omega=\bigl{(}0,\frac{1}{2}\bigr{)}^{2}roman_Ω = ( 0 , divide start_ARG 1 end_ARG start_ARG 2 end_ARG ) start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT**B**: Given**C**: Since all four corners
of ΩΩ\Omegaroman_Ω are π/2𝜋2\pi/2italic_π / 2, we have μ=(1,1,1,1)𝜇1111\mu=(1,1,1,1)italic_μ = (... | ACB | ABC | BAC | CBA | Selection 1 |
**A**: Its inputs are actions 𝐀𝐜𝐭𝐀𝐜𝐭\mathbf{Act}bold_Act, the maximum length 𝗅𝖾𝗇𝗅𝖾𝗇\mathsf{len}sansserif_len, a blockchain state 𝗊𝗊\mathsf{q}sansserif_q, and a threshold number of iterations 𝗇𝗇\mathsf{n}sansserif_n**B**: Its outputs are attack vectors that yield positive profits.
**C**: Algorithm 1 Atta... | CBA | BCA | CBA | ABC | Selection 2 |
**A**: [39]**B**: In VariBAD, a variational autoencoder (VAE) is used to learn a low-dimensional latent representation of the task distribution, and a deep neural network is trained to approximate the Bayes optimal policy. We show that by estimating the task distribution using our kernel density estimation method, appl... | ACB | BCA | BAC | BAC | Selection 2 |
**A**: Subsequently, using a word embedding technique, the word semantic space learning module determines the word vector space of each language from collected corpora. To compare words in a language-agnostic way, the space alignment module pairs up the spaces across languages utilizing a set of bilingual medical trans... | BAC | BAC | CAB | ACB | Selection 3 |
**A**: For saliency analysis, the absolute values of the gradients of prediction probabilities with respect to input pixels were calculated using the backward() method of pytorch during a backward pass.**B**: The pre-trained ViT model was pulled from the timm python library**C**:
Training and inference using ViT was i... | BCA | CBA | CAB | ABC | Selection 2 |
**A**: Bounded model checkers such as ESBMC are now mature software, used industrially (Gadelha et al., 2018) and capable of finding bugs in production software. We leverage this power of model checkers as a method for seed generation**B**: We evaluate seeds based on two criteria—the depth of the seed’s deepest goal an... | BCA | ABC | ACB | BCA | Selection 3 |
**A**: We shall use high-precision computation [5] in the Julia programming language888See https://julialang.org/ and https://docs.julialang.org/en/v1/manual/integers-and-floating-point-numbers/#Arbitrary-Precision-Arithmetic due to the instability of our algorithms for computing fractional integration matrices, which ... | ACB | BCA | ABC | CBA | Selection 3 |
**A**: Indeed, all 21 indexes in this study assign the value 0 to entities that do not hold the feature they are designed to quantify. There could be exceptions**B**: Currently, there is no unified rule on what value should be the lowest. In the main text, we consider the lowest value to be zero**C**: For example, one ... | BCA | ACB | ABC | BAC | Selection 4 |
**A**: We update the last two blocks of the MCUNet [47] model and only 1/4 of the weights for each layer to compare the accuracy of different channel selection methods (larger magnitude, smaller magnitude, and random)**B**: The results are quite similar (within 0.2% accuracy difference)**C**: Channel selection is not v... | ABC | ACB | BAC | BCA | Selection 1 |
**A**: A=(aij)𝐴subscript𝑎𝑖𝑗A=(a_{ij})italic_A = ( italic_a start_POSTSUBSCRIPT italic_i italic_j end_POSTSUBSCRIPT ) is called an M𝑀Mitalic_M-matrix if**B**: Then we denote
|A|=(|aij|)𝐴subscript𝑎𝑖𝑗|A|=(|a_{ij}|)| italic_A | = ( | italic_a start_POSTSUBSCRIPT italic_i italic_j end_POSTSUBSCRIPT | )**C**: Let ... | ABC | CAB | CBA | BAC | Selection 3 |
**A**: The travelling salesman problem is the classic hard problem of this type, the Eulerian cycle problem is a polynomial-time solvable example. We note that the order and adjacency types were, also under these names, already described in [ES15, p. 68]. Due to the different nature of these types of problems, it appea... | BAC | CBA | CAB | ACB | Selection 3 |
**A**:
where BI(v)𝐵𝐼𝑣BI(v)italic_B italic_I ( italic_v ) is the standard bilinear interpolation operator**B**: We used PyLops222https://github.com/PyLops/pylops, the linear operator library for Python, for performing bilinear interpolation and its transpose operation**C**: Consequently, the grid transfer operator... | ABC | BCA | ACB | CAB | Selection 1 |
**A**:
We focused on the threshold activation function**B**: It is an interesting direction to extend our results for other activation functions such as sigmoids**C**: For the universality result of depth 4 monotone networks it seems plausible that one could approximate thresholds by sigmoids and prove that monotone n... | BAC | ABC | BAC | CAB | Selection 2 |
**A**: Randomization of QMC rules also enables the computation of practical error estimates. These features make QMC methods ideal for heavy-duty uncertainty quantification compared to regular Monte Carlo methods (slow convergence rate) or sparse grids (not easily parallelizable). QMC methods have been applied successf... | CAB | ACB | BAC | ACB | Selection 1 |
**A**: In each round, each agent takes a sequence of pulls (one at each time step) and observes the outcomes**B**: At the end of the last round, all agents have to output the same answer without any further communication. The goal of BAI in the CL model is for all agents to output the correct answer with the smallest e... | ABC | BAC | ACB | ABC | Selection 3 |
**A**: It is noteworthy that the aforementioned algorithms are applicable in (strongly) convex cases. However, within the nonconvex nonsmooth setting, the algorithm proposed by [71] stands out with global convergence guarantees when the nonsmooth term is convex.
**B**: Conversely, the approach introduced in [59] also e... | BAC | CBA | CAB | ACB | Selection 2 |
**A**: The proposed algorithm is presented in Section IV with a detailed discussion on its properties. The computational complexity analysis is presented in Section V. Simulation results are presented in Section VI and a conclusion is given in Section VII.
**B**: Section III is devoted to introducing the tensor SVD, te... | BAC | ACB | CAB | CBA | Selection 4 |
**A**:
As discussed previously, semi-supervised random forests improve over supervised ones in fewer cases as compared to single trees**B**: A statistically significant improvement over CLUS-RF is observed only for the MLC task with 200 labeled examples and the HMLC task with 350 labeled examples**C**: However, in non... | ACB | BAC | BAC | ABC | Selection 4 |
**A**: Then, the controller is equipped with two decision-makers that predict waypoints and navigational controls to consider different aspects of driving. For a comparative study, we use AIM-MT as a baseline in justifying the performance of DeepIPC. The objective is to compare our model (that has a better data represe... | BCA | ACB | BCA | CBA | Selection 4 |
**A**: Recall that the task of 3333-Coloring is to decide whether a graph G𝐺Gitalic_G admits a proper 3333-coloring, that is, its vertices can be colored by three colors in such a way that adjacent vertices receive distinct colors**B**:
We reduce from the 3333-Coloring problem**C**: Equivalently, | BAC | ABC | BCA | CBA | Selection 1 |
**A**: For example, to achieve 65.0% accuracy on CIFAR, VAFL needs 5381.4 MB while VIMADMM only requires 124.54 MB, which is about 43x lower costs**B**: Here we use τ=20,30,20,5𝜏2030205\tau=20,30,20,5italic_τ = 20 , 30 , 20 , 5 for the four datasets respectively.
(3) The results under w/o model splitting setting demon... | ACB | BAC | BCA | CBA | Selection 3 |
**A**: 4, the variance σ2superscript𝜎2\sigma^{2}italic_σ start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT of the Gaussian noise is set to 0,0.01,0.0300.010.030,0.01,0.030 , 0.01 , 0.03, and 0.10.10.10.1 from left to right. The red point is the central node, into which we add the above noise**B**: The noisy information woul... | CBA | BCA | ABC | CAB | Selection 2 |
**A**: Ltd. His research interests include gait recognition, object detection and image segmentation.**B**: Xu Liu
received the B.E. and Ph.D**C**: degrees from University of Science and Technology of China in 2013 and 2018, respectively. He is currently a Research Scientist with Watrix Technology Limited Co | ACB | BCA | CAB | ACB | Selection 3 |
**A**: In this work, we propose dynamic partial average (DPAV), a novel approach to mitigate the overestimation problem specifically for the task-completion dialogue policy**B**: DPAV utilizes the partial average between the predicted maximal action value and the predicted minimal action value to estimate the ground tr... | CAB | CBA | CAB | ABC | Selection 4 |
**A**: Then, we define an out-of-context error as predicting a verb or a noun which is unseen in a given intention. For instance, if the model predicts the action ‘drive bike’ in a video where the human intention is ‘washing a dog’, we claim that the model has an out-of-context error**B**: Moreover, we further evaluate... | BCA | CAB | CAB | BAC | Selection 4 |
**A**: the contaminated training data.
Particularly, we can design a new learning objective embedded with the uncertainty concept. It adaptively penalizes uncertain predictions, while simultaneously encouraging more confident predictions to ensure effective learning of hard samples. Therefore, this process can discrimi... | CBA | CAB | BAC | BCA | Selection 2 |
**A**:
In this section, we take a deeper look into the specifics of evaluation for D2T systems. Traditionally, the evaluation of D2T systems is compartmentalized into either intrinsic or extrinsic measures (Belz and Reiter, 2006). The former either uses automated metrics to compare the generated narrative to a referen... | CAB | ACB | CAB | CAB | Selection 2 |
**A**: This far exceeds the performance of using only label correction or label smoothing methods (e.g., 3.9% ∼similar-to\sim∼ 4.7% absolute gains on metric Mean)**B**: The effectiveness of our proposed methods may be attributed to the ability to identify noisy samples for each predicate, as they operate on the entire ... | BAC | BCA | ACB | CAB | Selection 2 |
**A**: For this purpose, it can take advantage of the zero-knowledge contingent payment (ZKCP) protocol [campanelli2017zero]**B**: If the attacker does not want to share the block information with every miner, it can also share the partial block data b𝑏bitalic_b with a specific miner**C**: We propose an example block-... | ABC | BAC | ACB | CBA | Selection 2 |
**A**:
Figure 9: Zoom in on 200 steps of training**B**: The red vertical lines mark the moments at which the preconditioned sharpness crosses the stability threshold. **C**: For two learning rates from Figure 9 (top row = 5e-5, bottom row = 2e-4), we zoom in on 200 steps of training, plotting five important quantities | CBA | ABC | ACB | BCA | Selection 3 |
**A**: To account for the manifold density, we need to employ a density-preserving kernel**B**: Specifically, let us consider the pairwise transition probabilities based on an anisotropic diffusion kernel given by 36:
**C**: In contrast to Laplacian eigenmaps that are appropriate for data sampled uniformly 29, 35, diff... | CAB | BAC | CAB | ACB | Selection 4 |
**A**: (a) The mean radius condition is applied; there are 47 connected segments and 21 disconnected. (b) A proportion threshold is set to 0.8 and applied; there are 26 connected segments and 21 disconnected. (c) A single point threshold is applied to yield a connected tree of 75 connected segments and 53 disconnected.... | ACB | CBA | BAC | BAC | Selection 2 |
**A**: Based on the above results, one can see that our model outperforms all baselines in terms of accuracy, inference speed and generalization ability to open-world input.
For Table IV, we observed that our model outperforms in terms of accuracy**B**: One can observe that other well-studied GNN benchmark (i.e:DGCN) c... | ABC | CBA | CAB | ACB | Selection 4 |
**A**: The benchmark Atari 100K only allows the agent to interact with the environment for 100K steps**B**: Such a setup aims to test the sample efficiency of RL algorithms.**C**:
In our experiments, we use Atari 100K (Kaiser et al., 2020) benchmark for evaluation, which contains 26 Atari games from various domains | BCA | ACB | BAC | CBA | Selection 1 |
**A**:
The remainder of this paper is structured as follows. In Section 2, we introduce the MV-SDE and associated notation, motivate MC methods to estimate expectations associated with its solution and set forth the problem to be solved**B**: In Section 3, we introduce the decoupling approach for MV-SDEs (dos Reis et ... | ABC | ACB | ACB | CBA | Selection 1 |
**A**: It is safe to assume that in the preliminary environment characterization, the spacecraft would be able to determine if the environment tends or not to be a solar radiation pressure-dominated one or if the body is elongated. We can then rely on consolidated results in the literature [40, 38, 39] to propose that ... | CAB | BCA | ABC | ABC | Selection 2 |
**A**: We discuss this observation in more detail below.**B**: To our knowledge, this is the first work that analyzes the computation of Brascamp–Lieb constants via Thompson geometry.
We note that a similar Finslerian lens can be employed to understand other Picard iterations arising from problem (1.3)**C**: Our analys... | CBA | BAC | BCA | BCA | Selection 1 |
**A**: This is because any homologous cycle can represent a class, leading to a large number of potential pairings to explore. Corollary 2.19 aims to reduce the number of pairings that need to be checked for merging. It leverages the concept of k𝑘kitalic_k-nearness between cycles representing classes.
**B**: However, ... | BCA | CBA | BCA | BAC | Selection 2 |
**A**: To bridge this gap, Zhao et al. (Zhao_2022_CVPR, ) put forward a new SSL learning framework, named Distribution Consistency SSL, which rectifies the pseudo-labels from a distribution perspective.
Differently, Oh et al. (Oh_2022_CVPR, ) propose a general pseudo-labeling framework that class-adaptively blends the ... | ACB | CAB | ABC | BCA | Selection 2 |
**A**:
In this work, we propose Conv-Adapter, a parameter efficient tuning module for ConvNets**B**: Extensive experiments on classification and dense prediction tasks show it can achieve performance comparable to full fine-tuning with much fewer parameters. We find Conv-Adapter might fail on tasks with large domain s... | ABC | CAB | ABC | ACB | Selection 4 |
**A**: Existing PINNs methods face challenges in managing abrupt variations or discontinuities in dynamical systems**B**: Such changes often signal shifts in system dynamics or the influence of external factors**C**: For example, detecting leakages in pipelines using limited sensor data [18]; traffic flow management by... | BCA | BCA | BAC | ABC | Selection 4 |
**A**: In between, a range of hybrid methods can be positioned. The comparison is of course not straightforward but conceptual; for example, some information can be computed online or offline, and some methods require sequential computations whereas others can do things simultaneously in parallel.**B**:
As a consequen... | BAC | CAB | BCA | ACB | Selection 2 |
**A**: In addition, including other types of relationships outside of parent-child relationships, such as synonyms, could be of interest. Furthermore, including more means to show the data distribution could help in the process of creating the label hierarchy.**B**: To further include object localization tasks, an addi... | BAC | CBA | BCA | BAC | Selection 2 |
**A**:
Dacheng Tao (F’15) is currently a Distinguished University Professor in the College of Computing & Data Science at Nanyang Technological University**B**: He mainly applies statistics and mathematics to artificial intelligence and data science, and his research is detailed in one monograph and over 200 publicat... | BAC | ABC | BAC | CAB | Selection 2 |
**A**: Categories of generic domains (e.g., .net, .com) are identified by direct visits (via Russian IP relays) or querying Internet archives if they are down**B**: Some targets were indeed down while previously active, suggesting attacks might have succeeded e.g., ksrf.ru (the Constitutional Court of the Russian Feder... | BAC | BCA | ACB | BAC | Selection 2 |
**A**:
Identifying the top k𝑘kitalic_k samples is not only useful for the attacker, but also the defender**B**: We call this performance measure the transferability at k𝑘kitalic_k defined as**C**: This is because a defender can evaluate his or her model’s robustness to attacks given the attacker’s best efforts (atta... | ABC | BCA | ACB | CBA | Selection 3 |
**A**: The problem of exponential concentration for the fidelity quantum kernel was first observed in Ref. [6] and later analyzed in Ref. [7, 44, 45] in the context of generalization. Ref. [7] discusses exponential concentration in the context of a projected quantum kernel for a specific example embedding.
On the othe... | ABC | BCA | CBA | ACB | Selection 4 |
**A**: : The second method is designed over the first one**B**: Bounding box information is embedded to each frame of the RGB video data to improve classification and prediction accuracy. This method assumes that a separate vehicle prediction method has been used on the RGB input frames, prior to our lane change predic... | BAC | BCA | BAC | ACB | Selection 4 |
**A**: Norm.Imit.Obf. IObf**B**: II00\displaystyle 011\displaystyle 11Accuracy (GH)Abuhamad et al.Caliskan et al.GuessingOriginal
Figure 5. Attribution performance (accuracy) of candidate techniques**C**: II00\displaystyle 011\displaystyle 11Accuracy (GCJ)Norm.Imit.Obf. IObf | CAB | ACB | BCA | ABC | Selection 2 |
**A**: For General-10, the same evaluation metrics to CLIP are used. For all tasks of Plant-6, RS-8 and Fashion-20, top-1 accuracy is adopted. Besides linear probe and zero-shot recognition, test set metrics of the last checkpoint are reported, thus no validation is involved.**B**: For few-shot classification, to reduc... | ACB | BAC | CBA | BAC | Selection 3 |
**A**: In scenarios such as causal or anti-causal tasks, where a more specific causal graph structure is deemed essential, our proposed causal graph might stand out as a flexible and adaptable framework. It may serve not only as a solution for domain adaptation but also as a source of inspiration for various tasks**B**... | BCA | BAC | BAC | CAB | Selection 1 |
**A**: Recall that MFG PDE systems are derived from models of large numbers of players solving stochastic optimal control problems**B**: We now outline the motivation for the present paper**C**: It is well-known from stochastic optimal control that, in many applications of practical interest, the underlying controls ma... | ACB | CBA | ACB | BAC | Selection 4 |
**A**:
It is easy to see that if all players consider all possible subsets of all channels in the bundles for they submit their bids, the solution of 4 coincides with the solution of 3. However, even in the case of relatively low total number of channels (e.g**B**: 15), this results in computationally infeasible probl... | BAC | ABC | ACB | BAC | Selection 2 |
**A**: The forecasting quality drops off with too many heads n=16𝑛16n=16italic_n = 16.
(4) Representation dimension d𝑑ditalic_d: The representation dimension of inputs and temporal factors in TCVAE highly determines the parameter effectiveness in temporal factor guidance and the capability of the learned representati... | ABC | ACB | CAB | BCA | Selection 4 |
**A**: Here we focus specifically on introducing priors corresponding to overdamped Langevin dynamics, deeply driven by the principles of statistical mechanics**B**: Nevertheless, we anticipate the framework should be easily generalized to other physics-based dynamics models**C**: For the widely adopted model of Browni... | ABC | CBA | BCA | CAB | Selection 1 |
**A**: In [56], the energy consumption of a quadrotor is modeled as:**B**: Regarding the energy consumption of the quadrotor, there are electric models and physics-based models that are derived using approaches similar to those used for the WMR**C**:
More complex models are also possible, which consider external distu... | ACB | ABC | CBA | ABC | Selection 3 |
**A**:
Previous work went beyond this paper in other aspects, however**B**: Given a concrete model such as Gaussian VAEs, convergence to entropies was also numerically investigated**C**: It was for instance asked, how close the original ELBO is to the sum of entropies result in practice, i.e., when only the vicinity o... | BCA | CAB | ABC | BAC | Selection 3 |
**A**: Our work makes heavy use of graph subdivisions as well, although in a more sophisticate fashion. This is not surprising since, for each d≥2𝑑2d\geq 2italic_d ≥ 2, the class of d𝑑ditalic_d-degenerate graphs constitutes an example of a monotone somewhere dense class of graphs.
**B**: For example, [5] observed tha... | CBA | ABC | CAB | ABC | Selection 1 |
**A**: By doing intervention on items and adjusting popularity bias during the inference stage, PDA gets better recommendation accuracy**B**: Nevertheless, it still performs worse than ESMM-RT and MBD because of ignoring the relations between item quality and popularity.
**C**: PDA shows better results than MACR, Multi... | CBA | ABC | BCA | BAC | Selection 3 |
**A**: We compare the proposed method with both handcrafted feature based methods including NIQE [25], IL-NIQE [73], BRISQUE [26], DIIVINE [28], CORNIA [39], HOSA [74], BQMS [75], SIQE [15], ASIQE [15], NRLT [16], and deep-learning based methods including DIQaM-NR [64], WaDIQaM-NR [64], PQSC [76], RIQA [58], MtDI [22] ... | CAB | ABC | BAC | BCA | Selection 1 |
**A**: To measure the level of homophily, several homophily measures are used in the literature [1, 20, 32, 48], but these measures may significantly disagree with each other. In this work, we start by addressing the problem of how to properly measure the homophily level of a graph**B**: For this, we formalize some des... | ABC | ACB | BAC | BAC | Selection 1 |
**A**: Section 3 is devoted to the statement and proof of our main results, namely a quantum L1superscript𝐿1L^{1}italic_L start_POSTSUPERSCRIPT 1 end_POSTSUPERSCRIPT-Poincaré inequality (Theorem 3.1), quantum Talagrand inequality (Theorem 3.2), and quantum KKL theorem (Theorem 3.9) and a quantum Friedgut’s Junta theor... | CBA | CAB | BAC | CAB | Selection 3 |
**A**: This fine-grained formalization of PA-Boot in Isabelle/HOL succinctly captures its key components, the system behaviors, and a full range of adversarial capabilities against the protocol**B**: To the best of our knowledge, PA-Boot is the first formally verified processor-authentication protocol for secure boot i... | ACB | CAB | BAC | ABC | Selection 4 |
**A**: In this paper, a general notion of dissipativity with dynamic supply rates was introduced for nonlinear systems, extending the notion of classical dissipativity**B**: In these results, both dynamical systems are characterised by compatible dissipation inequalities with respect to “coupled”**C**: Lyapunov and asy... | CAB | ABC | ACB | CAB | Selection 3 |
**A**: also claim that a state-feedback law achieving safety with probability one often diverges toward the boundary of the safe set; the inference is also obtained from the fact that the conditions for the existence of an invariance set in a stochastic system are strict and influenced by the properties of the diffusio... | CBA | BCA | ABC | CAB | Selection 4 |
**A**:
Participants paired with our legible policy saw an increase of 15% in correct predictions, taking on average 3333 seconds less to predict the robot’s objective**B**: These two aspects support the usefulness of this type of policy in interaction scenarios between humans and robots: by causing humans to have be... | BCA | BCA | ABC | BCA | Selection 3 |
**A**: Random variables are in capital case (e.g**B**: X𝑋Xitalic_X), and their realization are in lower case (e.g**C**: x𝑥xitalic_x). All random variables take values in some alphabets that are in calligraphic letters (e.g. 𝒳𝒳\mathcal{X}caligraphic_X).
We shall restrict our attention to finite alphabets only. | ACB | BCA | ABC | ACB | Selection 3 |
**A**: Here CgSCRCgSCR{\rm CgSCR}roman_CgSCR denotes the critical gSCRgSCR\rm gSCRroman_gSCR, defined as the value of SCR that renders a wind farm critically stable in a single-wind-farm-infinite-bus system**B**: A larger gSCR indicates a larger stability margin.**C**: When all the wind farms in Fig. 4 adopt GFL contro... | ACB | ACB | BAC | BCA | Selection 4 |
**A**: We can see that even with a relatively high order k=9𝑘9k=9italic_k = 9, the trend functions missed a few peaks and troughs in the data. In other words, there appears to be over smoothing.
**B**: 1**C**: Fig. 2 shows polynomial trends estimated together with VAR(4444) coefficients for the series in Fig | BAC | CBA | BCA | ACB | Selection 2 |
**A**: The unknown class can be constituted by a diverse set of semantic classes, but is regarded as a single chunk. The known classes must have no semantic overlap with the unknown class.
**B**: Datasets. For the empirical analysis, we test on the standard OSR datasets as described in Protocol A of Sec**C**: 6.1. Each... | CBA | CBA | CAB | CBA | Selection 3 |
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