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**A**: Thus recording the row and and column operations required to transform a diagonal matrix into the identity, allows us to write the input matrix as a product of transvections. **B**: Note that row and column operations are effected by left- and right multiplications by transvections**C**:
The key idea is to tran... | ABC | BAC | CBA | BAC | Selection 3 |
**A**:
It is essential for the performing method that the static condensation is done efficiently**B**: We note that the idea of performing global static condensation goes back to the Variational Multiscale Finite Element Method–VMS [MR1660141, MR2300286]. Recently variations of the VMS**C**: The solutions of (22) dec... | ACB | BCA | CAB | CBA | Selection 1 |
**A**: Moreover, Alg-A is more stable than the alternatives.
During the iterations of Alg-CM, the coordinates of three corners and two midpoints of a P-stable triangle (see Figure 37) are maintained**B**: Alg-CM uses an involved subroutine (far more complicated than ours given in Algorithm 1) to update the coordinates ... | ACB | CBA | BCA | CAB | Selection 1 |
**A**: CrowdWisdom: Similar to [18], the core idea is to leverage the public’s common sense for rumor detection: If there are more people denying or doubting the truth of an event, this event is more likely to be a rumor. For this purpose, [18] use an extensive list of bipolar sentiments with a set of combinational ru... | ACB | CBA | BAC | BAC | Selection 1 |
**A**: However, if we initialize with η<1/ℒ(𝐰(0))𝜂1ℒ𝐰0\eta<1/\mathcal{L}(\mathbf{w}(0))italic_η < 1 / caligraphic_L ( bold_w ( 0 ) ) then it is straightforward to show the gradient descent iterates maintain bounded local smoothness**B**: Assumption 1 includes many common loss functions, including the logistic, exp... | BAC | CBA | ACB | CAB | Selection 1 |
**A**: Furthermore, we would expect that verified users are less involved in the rumor spreading. However, the feature appears near-bottom in the ranked list, indicating that it is not as reliable as expected. Also interestingly, the feature“IsRetweet” is also not as good a feature as expected, which means the probabil... | BAC | ABC | ACB | CBA | Selection 4 |
**A**: We use the unigram model with default Dirichlet smoothing.
**B**: We model 𝖽(e)𝖽𝑒\mathsf{d}(e)sansserif_d ( italic_e ) as the corresponding Wikipedia article text**C**: Language Model-based, how likely aspects are generated by as stastical LM based on the textual representation of the entity 𝖽(e)𝖽𝑒\maths... | CBA | ACB | ABC | ABC | Selection 1 |
**A**:
Table 1 shows basic patient information. Half of the patients are female and ages range from 17 to 66, with a mean age of 41.8 years**B**: Body weight, according to BMI, is normal for half of the patients, four are overweight and one is obese. The mean BMI value is 26.9**C**: Only one of the patients suffers fr... | CAB | BAC | CAB | ABC | Selection 4 |
**A**:
This study has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement Nos**B**: Furthermore, we gratefully acknowledge the support of NVIDIA Corporation with the donation of a Titan X Pascal GPU used for this research.**C**: 720... | BCA | ACB | BCA | CBA | Selection 2 |
**A**:
We call a marking sequence σ𝜎\sigmaitalic_σ for a word α𝛼\alphaitalic_α block-extending, if every symbol that is marked except the first one has at least one block-extending occurrence**B**: This definition leads to the general combinatorial question of whether every word has an optimal marking sequence that ... | ABC | CAB | CAB | ACB | Selection 1 |
**A**:
The main loop in Algorithm 1 is iterated 15151515 times (cf**B**: The world model is trained for 45454545K steps in the first iteration and for 15151515K steps in each of the following ones. Shorter training in later iterations does not degrade the performance because the world model after first iteration captu... | ACB | CAB | BAC | BCA | Selection 1 |
**A**: This ensured robust management of the robot’s intricate dynamics and interactions**B**: In order to account for the robot’s dynamics and precisely quantify energy consumption during step negotiation, we utilized the Vortex physical engine incorporated within CoppeliaSim (previously known as V-REP) robotics simul... | BAC | CBA | ACB | CAB | Selection 1 |
**A**:
In future work, we would like to expand the model so as to incorporate, into the analysis, the concept of advice error**B**: In this setting, the objective would be to study the power and limitations of online algorithms, i.e., from the point of view of both upper and lower bounds on the competitive ratio. A fi... | CAB | ABC | ACB | ABC | Selection 3 |
**A**: With this goal in mind, we also carried out an error analysis and identified four common error cases which could be divided into two groups: those that arise from bad labeling of the test set and those that arise from bad classifier performance**B**: In Figure 8 we exemplify each case with one subject from the t... | ACB | CBA | ACB | BCA | Selection 4 |
**A**: We can find that both local momentum and global momentum implementations of DMSGD are equivalent to the serial MSGD if no sparse communication is adopted**B**: However, when it comes to adopting sparse communication, things become different**C**: In the later sections, we will demonstrate that global momentum is... | ABC | ACB | CBA | CBA | Selection 1 |
**A**: operation.**B**:
, where ∗*∗ is the convolution333We use convolution instead of cross-correlation only as a matter of compatibility with previous literature and computational frameworks**C**: Using cross-correlation would produce the same results and would not require flipping the kernels during visualization | CBA | BAC | CAB | ACB | Selection 3 |
**A**: Higher altitude indicates larger coverage size as shown in Fig. 1 (c)**B**:
In order to support as many users as possible, UAVs are required to enlarge coverage size, which is equal to enlarge the coverage proportion in the mission area**C**: The utility of coverage size is denoted as | BAC | CBA | BCA | CAB | Selection 1 |
**A**: The vector of nodal**B**: Similarly, the axial centroid coordinates
are defined as z^=<z¯>e^𝑧superscriptexpectation¯𝑧𝑒\widehat{z}=<\overline{z}>^{e}over^ start_ARG italic_z end_ARG = < over¯ start_ARG italic_z end_ARG > start_POSTSUPERSCRIPT italic_e end_POSTSUPERSCRIPT**C**: radial coordinates of the nodes | ABC | CBA | ACB | CAB | Selection 2 |
**A**: However, our experiments were limited to simple problems and environments, utilizing small network architectures and only two Dropout methods.
**B**: Our findings indicate that the Dropout-DQN method is effective in decreasing both variance and overestimation**C**: In this study, we proposed and experimentally a... | CBA | CAB | BCA | BCA | Selection 1 |
**A**:
Exploring reinforcement learning approaches similar to Song et al**B**: (2018) and Wang et al**C**: (2018c) for semantic (medical) image segmentation to mimic the way humans delineate objects of interest. Deep CNNs are successful in extracting features of different classes of objects, but they lose the local sp... | CBA | BAC | BCA | ABC | Selection 4 |
**A**: The classifier follows the same overall setup, i.e., 500500500500 decision trees and a maximum depth of ten.
**B**: RF: Random forest (Breiman, 2001) is an ensemble-based method consisting of multiple decision trees**C**: Each decision tree is trained on a different randomly selected subset of features and sampl... | CBA | BAC | CAB | CBA | Selection 3 |
**A**: To answer this question, we propose the first policy optimization algorithm that incorporates exploration in a principled manner. In detail, we develop an Optimistic variant of the PPO algorithm, namely OPPO**B**: Our algorithm is also closely related to NPG and TRPO. At each update, OPPO solves a Kullback-Leibl... | BAC | ABC | BAC | CBA | Selection 2 |
**A**: (2018b), weights, activations, weight gradients, and activation gradients are subject to customized quantization schemes that allow for variable bit widths and facilitate integer arithmetic during training and testing.
In contrast to Zhou et al**B**: In Wu et al**C**: (2016), the work of Wu et al. (2018b) accumu... | ABC | BAC | ACB | ABC | Selection 2 |
**A**: Also, every compact, (topologically) finite dimensional, and locally contractible metric space is ANR (see [34, Section 1]). The following example is one application of this fact.
**B**: Not only that, every locally Euclidean metric space is an ANR (see [51, Theorem III.8.1])**C**: It is known that every topolog... | CAB | BAC | BAC | CBA | Selection 4 |
**A**: Irregularly-shaped clusters are also of interest [14], which suggests that the points’ organization along a non-linear multidimensional axis might be relevant. The problem of explaining the reasons why those clusters are formed is tackled by a number of t-viSNE views that are described next.
**B**: Having establ... | CAB | CBA | ABC | BAC | Selection 1 |
**A**: As we have mentioned, we must emphasize that in these new algorithms, there exists a lack of justification together with the lack of comparison with the state of the art and of real interest in achieving reasonable levels of quality from the point of view of the optimization of well-known problems in recent comp... | BCA | ACB | BAC | CAB | Selection 3 |
**A**: GAEs proposed in [20, 29, 22] intend to reconstruct the adjacency via decoder while GAEs developed in [21] attempt to reconstruct the content**B**: The difference is which extra mechanism (such as attention, adversarial learning, graph sharpness, etc.) is used.**C**: To apply graph convolution on unsupervised le... | CAB | ABC | CBA | BCA | Selection 4 |
**A**: Recently, (Ensafi et al., 2014; Pearce et al., 2017) developed statistical methods for measuring IPID. However, in contrast to our work, the goal in (Ensafi et al., 2014; Pearce et al., 2017) is different - they use IPID to measure censorship and have additional sources of inaccuracy, which do not apply to our m... | BAC | ACB | BCA | ACB | Selection 3 |
**A**: It reuses weights and biases across the steps of a sequence and can thus process variable-length sequences**B**:
The context pathway is based on a recurrent neural network (RNN) approach**C**: The alternative was to use a long-short term memory (LSTM), which employs gating variables to better remember informati... | BAC | CAB | ABC | CAB | Selection 1 |
**A**: As an example, we prove in the following theorem that it is possible to adjoin a free generator to every self-similar semigroup without losing the self-similarity property and that the analogous statement for automaton semigroups holds as well**B**: The construction used to prove Theorem 6 can also be used to ob... | CBA | BAC | BCA | CBA | Selection 2 |
**A**: Table A4 shows VQA accuracy for each answer type on VQACPv2’s test set. HINT/SCR and our regularizer show large gains in ‘Yes/No’ questions**B**: We hypothesize that the methods help forget linguistic priors, which improves test accuracy of such questions. In the train set of VQACPv2, the answer ‘no’ is more fre... | ABC | CBA | CAB | CAB | Selection 1 |
**A**: (2014), but issues of accuracy, scalability and generalization remain. More importantly, annotations in the privacy policy domain are expensive. Privacy policies are difficult to understand and many tasks such as privacy practice classification (Wilson et al., 2016), privacy question answering (Ravichander et al... | CBA | ACB | BCA | ABC | Selection 1 |
**A**: For our example in Figure 4(a), they are enabled.**B**: Permutation feature importance is measured by observing how random re-shuffling of each predictor influences model performance.
Accuracy feature importance removes features one by one, similar to permutation, but then retrains each model by receiving only t... | BCA | CAB | ABC | ACB | Selection 2 |
**A**: small data sets) to get a parameter initialization which is easy to adapt to target tasks with a few samples. As a model-agnostic framework, MAML is successfully employed in different NLP applications.
Some works use MAML for few-shot text classification, such as relation classification [Obamuyide and Vlachos, 2... | CBA | CAB | ACB | BAC | Selection 1 |
**A**: The uniform linear array (ULA) and uniform planar array (UPA) are widely adopted in the existing studies on mmWave communication and networking [12, 13, 14, 15]. However, their coverage capabilities are often confined within a two-dimensional space and a half three-dimensional space. Therefore, conventional ULA ... | CAB | ACB | ABC | ACB | Selection 1 |
**A**: We**B**: Note that the 1111-color case with the completeness requirement is not very interesting, and also not useful for the general case: completeness states that every node on
the left must be connected, via the unique edge relation, to every node on the right – regardless of the matrix**C**: This will be boo... | ACB | BAC | CBA | ABC | Selection 3 |
**A**: We remark that our analysis straightforwardly generalizes to the setting where ‖x‖≤Cnorm𝑥𝐶\|x\|\leq C∥ italic_x ∥ ≤ italic_C for an absolute constant C>0𝐶0C>0italic_C > 0.
**B**: Assumption 4.1 can be ensured by normalizing all state-action pairs**C**: Such an assumption is commonly used in the mean-field ana... | CAB | CBA | BCA | BAC | Selection 1 |
**A**: Given that the depth-wise LSTM unit only takes one input, we introduce a merging layer to merge the outputs of these two sub-layers into one as the input to the LSTM unit**B**:
Different from encoder layers, decoder layers involve two multi-head attention sub-layers: a masked self-attention sub-layer to attend ... | BAC | ACB | ACB | ABC | Selection 1 |
**A**: Apply [33, Corollary
5.14] to A𝐴Aitalic_A and B𝐵Bitalic_B**B**: furthermore B→C→𝐵𝐶B\to Citalic_B → italic_C**C**: Then A~⊧φmodels~𝐴𝜑\widetilde{A}\models\varphiover~ start_ARG italic_A end_ARG ⊧ italic_φ because A→A~→𝐴~𝐴A\to\widetilde{A}italic_A → over~ start_ARG italic_A end_ARG and | CAB | CBA | CAB | BAC | Selection 4 |
**A**:
In this work, we presented a new learning representation for the deep distortion rectification and implemented a standard and widely-used camera model to validate its effectiveness**B**: Like most of the assumptions in the other works [21, 23, 8, 11, 12, 14], our approach has two main limitations to extend to m... | ABC | ABC | BCA | ACB | Selection 4 |
**A**: We don’t use training tricks such as warm-up [7]**B**: SNGM achieves the best performance for almost all batch size settings.**C**: We adopt the linear learning rate decay strategy as default in the Transformers framework.
Table 5 shows the test accuracy results of the methods with different batch sizes | BCA | BCA | ACB | BAC | Selection 3 |
**A**: This new algorithm is intricate and may be of interest on its own.**B**:
We follow up with 3333-approximations for the homogeneous robust outlier MatSup and MuSup problems, which are slight variations on algorithms of [6] (specifically, our approach in Section 4.1 is a variation on their solve-or-cut methods)**... | CAB | CBA | BCA | CBA | Selection 1 |
**A**:
II**B**: The sequence of random digraphs is conditionally balanced, and the weighted adjacency matrices are not required to have special statistical properties such as independency with identical distribution, Markovian switching, or stationarity, etc. The edge weights are also not required to be nonnegative at... | BCA | BCA | ACB | BAC | Selection 3 |
**A**: Specifically, there are three main steps in the proposed approach. First, MuCo partitions the tuples into groups and assigns similar records into the same group as far as possible. Second, the random output tables, which control the distribution of random output values within each group, are calculated to make s... | ACB | CAB | BCA | BCA | Selection 1 |
**A**: During training process, the batch size is 8 (one image per GPU) and all BN statistics are freezed. Mixed precision training enables to reduce GPU memory. The input images are randomly resized to n×n𝑛𝑛n\times nitalic_n × italic_n, which is uniformly sampled from range [1200,1400]12001400[1200,1400][ 1200 , 140... | CAB | ABC | BAC | BCA | Selection 1 |
**A**: As was written in the previous version, an anonymous referee of version 1 wrote that the theorem was known to experts but not published**B**:
Here we give an embarrassingly simple presentation of an example of such a function (although it can be shown to be a version of the example in the previous version of th... | BCA | ABC | BAC | CBA | Selection 3 |
**A**: We first incorporated the epoch start strategy into LSVI-UCB algorithm (Jin et al., 2020) to propose the LSVI-UCB-Restart algorithm with low dynamic regret when the total variations are known. We then designed a parameter-free algorithm Ada-LSVI-UCB-Restart that enjoys a slightly worse dynamic regret bound witho... | BAC | ABC | BCA | BAC | Selection 3 |
**A**: In Singapore, there have been active efforts through campaigns from various organizations (e.g., S.U.R.E. (Board, [n.d.]), Better Internet (Council, [n.d.]), VacciNationSG (Lai, 2021)) to raise awareness on misinformation, disinformation and fake news. If it is through the exposure to the messages of these campa... | CBA | BCA | ABC | BCA | Selection 1 |
**A**: The computation involves the previous two layers and can be formulated using the following equation:
**B**: Alternatively, we can implement the decentralized approach using a second-order attention mechanism**C**: As depicted in 2b, each layer in DAN consists of two steps, similar to a multi-layer GAT | BCA | ABC | ABC | CAB | Selection 4 |
**A**: In section III-A, we introduce the theory of VDM based on conditional variational inference**B**: In section III-B, we present the detail of the optimizing process. In section III-C, we analyze the result of VDM used in ‘Noisy-Mnist’ that models the multimodality and stochasticity in MDP. In section III-D, we pr... | CBA | CBA | BCA | CBA | Selection 3 |
**A**: It is therefore inappropriate for
approximating strongly varying functions, such as the Runge function**B**: Further, we recognize that the Vandermonde approach is inaccurate and even becomes numerically unstable (rising errors) for higher degrees**C**: As expected, (Chebyshev) polynomial interpolation on unifor... | BAC | ACB | ACB | ABC | Selection 1 |
**A**: In the Appendix we present such implementations. where we significantly constrain the capacity of the learned representation and heavily regularize the model to produce independent factors. As we explained above, such a model will likely learn a good disentangled representation, however, its reconstruction will ... | CBA | CAB | BAC | ABC | Selection 3 |
**A**:
Exploration based on previous experiments and graph theory found errors in structural computers with electricity as a medium**B**: In short, the direction of current, which is the flow of electricity, is determined only by the height of the potential, not by the structure or shape of the circuit.**C**: The caus... | CBA | ABC | ACB | CAB | Selection 3 |
**A**:
A finite field, by definition, is a finite set, and the set of all permutation polynomials over the finite field forms a group under composition**B**: In this paper, we propose a representation of such a group using the concept of linear representation defined through the Koopman operator.**C**: Given a finite ... | ABC | ACB | CBA | ABC | Selection 2 |
**A**: If one additionally considers that NNFS does not scale well with larger problems there is generally no reason to choose this algorithm over the nonnegative (adaptive) lasso.**B**:
The NNFS algorithm performed surprisingly well in our simulations given its simple and greedy nature, showing performance very simil... | BCA | ABC | CAB | CBA | Selection 3 |
**A**: In terms of interpretability (point 2), a small, non-redundant, and strongly related set of relevant variables is beneficial for interpreting detected anomalies.Lastly, different feature selection methods have varying computational costs and scalabilities based on the number of variables and objects. Thus, compu... | CAB | ABC | ACB | CBA | Selection 1 |
**A**: We note that Ou et al**B**: [2018] also consider a similar problem of developing an online algorithm for the MNL model with linear utility parameters**C**: Though they establish a regret bound that does not depend on the aforementioned parameter κ𝜅\kappaitalic_κ, they work with an inaccurate version of the MNL ... | ABC | ACB | CAB | BAC | Selection 1 |
**A**:
Implementation Details. In order to achieve higher performance, some works directly process video frames and learn features for the task of temporal action localization (TAL) in an end-to-end fashion [24, 42]**B**: However, this has humongous requirements for GPU memory and computational capability. Instead, we... | ACB | CBA | ABC | ACB | Selection 3 |
**A**: The use of parallel coordinates plots [ID87] is rather prominent for the visualization of automatic hyperparameter tuners such as HyperOpt [BKE∗15]**B**: Visualizations arranged into dashboard-styled interfaces are the preferred norm for managing ML experiments and their associated models [SKJ∗17, TMB∗18, WRW∗20... | BAC | ACB | BAC | BCA | Selection 2 |
**A**: However, these algorithms may become computationally infeasible when dealing with swarms that comprise hundreds to thousands of agents.**B**: Additionally, [35] offers an overview of existing swarm robotic applications.
For swarm guidance purposes, certain deterministic algorithms have been developed in [36, 37,... | BAC | CBA | BAC | BAC | Selection 2 |
**A**: Due to the use of a sparse modelling approach, the method also has the disadvantage that only few points per shape are matched, see Fig. 1.
In [29], tensor maps are introduced for synchronising heterogeneous shape collections using a low-rank tensor decomposition formulation. The work [26] presents a self-superv... | CAB | BAC | ABC | CBA | Selection 4 |
**A**: We overcome this problem by visiting the connected components in a smart order. This order allows us to establish all the antipodality relations in a faster time. This is done in Step 4, Step 5, and Step 6 that are the core of algorithm RecognizePG.**B**: In a few words, an antipodality graph has as vertex set s... | ABC | ABC | CBA | ACB | Selection 3 |
**A**: DCSBM is widely used for community detection for non-mixed membership networks (zhao2012consistency, ; SCORE, ; cai2015robust, ; chen2018convexified, ; chen2018network, ; ma2021determining, ). MMSB constructed a mixed membership stochastic blockmodel (MMSB) which is an extension of SBM by letting each node have... | CAB | BCA | CAB | ACB | Selection 2 |
**A**: Our contribution is two fold**B**: First, utilizing the optimal transport framework and the variational form of the objective functional, we propose a novel variational transport algorithmic framework for solving the distributional optimization problem via particle approximation.
In each iteration, variational t... | CAB | BCA | ABC | ABC | Selection 2 |
**A**: MetaVIM learns the decentralized policy for each intersection which considers neighbor information in a latent way**B**: We conduct extensive experiments and demonstrate the superior performance of our method over the state-of-the-art. We have collected and released more complex scenarios containing different st... | CBA | CBA | ACB | BCA | Selection 4 |
**A**:
Online bin packing has a long history of study. The simplest algorithm is NextFit, which places an item into its single open bin when possible; otherwise, it closes the bin (does not use it anymore) and opens a new bin for the item**B**: FirstFit is another simple heuristic that places an item into the first bi... | BAC | CAB | CAB | ABC | Selection 4 |
**A**: To mitigate the issue, we add an edge length regularization motivated by (Wang et al., 2018)**B**:
The above formulation alone causes that many of the produced patches have unnecessarily long edges, and the network folds them, so the patch fits the surface of an object**C**: If we assume that the reconstructed ... | ABC | ABC | BAC | CAB | Selection 3 |
**A**: By using batching technique, the results can be generalized to stochastic saddle-point problems [15, 23]**B**: Instead of the smooth convex-concave saddle-point problem we can consider general sum-type saddle-point problems with common variables in more general form. For each group of common variable, we introdu... | BCA | CBA | CAB | CBA | Selection 1 |
**A**: Among these classes we can find the strictly fundamental class.**B**: In [6] the authors characterize them in terms of their corresponding cycle matrices and present a Venn diagram that shows their inclusion relations**C**:
Different classes of cycle bases can be considered | CAB | CBA | BAC | ACB | Selection 2 |
**A**: of Patáková [35, Theorem 2.3] into:
**B**: One immediate application of Theorem 1.2 is the reduction of fractional Helly numbers**C**: For instance, it easily improves a theorem444[35, Theorem 2.3] was not phrased in terms of (K,b)𝐾𝑏(K,b)( italic_K , italic_b )-free covers but readily generalizes to that setti... | CAB | ACB | ACB | ACB | Selection 1 |
**A**: Fig. 1(d)); and
(v) contrast the performances of the best predictive performance found so far vs**B**: the current result according to three validation metrics in Fig. 1(e).**C**: (iv) during the detailed examination phase, check the different transformations of the features with statistical measures and compare... | CAB | CBA | BCA | CBA | Selection 3 |
**A**:
Figure 5: Position, velocity, acceleration, and maximal contour error resulting from optimization of the MPC parameters, comparing unconstrained BO optimization (solid lines) to BO optimization with additional constraint on the maximal tracking error, for infinity (left) and octagon(center) geometries**B**: The... | CAB | ACB | BCA | CAB | Selection 2 |
**A**: So far, there is no study comparing methods from either group comprehensively. Often papers fail to compare against recent methods and vary widely in the protocols, datasets, architectures, and optimizers used**B**: For CelebA, [46] uses ResNet-18 whereas [50] uses ResNet-50, but the comparison was done without ... | ACB | BCA | CAB | CBA | Selection 1 |
**A**: They use a simple CNN and the performance surpasses most of the conventional appearance-based approaches.
Following this study, an increasing number of improvements and extensions on CNN-based gaze estimation methods emerged. Face images [42] and videos [43] have also been used for gaze estimation.**B**: Zhang e... | ABC | CBA | CAB | CAB | Selection 2 |
**A**: This behavior can be explained by the fact that VGG-16 features fail to ensure a high discriminative power comparing to the DRF features that are still relatively steady compared to their results on the real masked faces. When dealing with other state-of-the-art recognizers, one of them applied the same pre-trai... | BAC | ABC | BCA | CBA | Selection 3 |
**A**: Since they are not recursive, we do not bother tracking the size superscript of the typing judgment, since they can be inlined**B**: Moreover, we take the liberty to nest values (boxed and highlighted yellow), which can be expanded into SAX [PP20].**C**:
First, we define head and tail observations on streams of... | BCA | ACB | BAC | ACB | Selection 1 |
**A**: This means that FairCMS-I is more efficient at the cost of lacking IND-CPA security. Therefore, the trade-off between security and efficiency is evident.
**B**: For another, since M>T>L𝑀𝑇𝐿M>T>Litalic_M > italic_T > italic_L and δ>1𝛿1{\delta}>1italic_δ > 1, it is intuitive from Table II that in FairCMS-II, th... | ACB | ACB | ACB | CAB | Selection 4 |
**A**: (2016) use pre-trained factorization machines to create field embeddings before applying a DNN, while Product-based Neural Networks (PNNs) Qu et al**B**: Factorization-machine supported Neural Networks (FNNs) Zhang et al**C**: (2016) model both second-order and high-order interactions through the use of a produc... | CAB | CBA | ABC | BAC | Selection 4 |
**A**: Table 1:
Number of iterations needed to achieve an ε𝜀\varepsilonitalic_ε-optimal solution for Problem 1.1**B**: The oracles listed under the Requirements column are the additional oracles required, other than the first-order oracle (FOO) and the linear minimization oracle (LMO) which all algorithms use.**C**: ... | CAB | ACB | ABC | BCA | Selection 2 |
**A**: Nevertheless, we show how to set parameters so that putting on hold DFS over large trees increases the number of passes only by a poly1/εpoly1𝜀\operatorname{poly}1/\varepsilonroman_poly 1 / italic_ε factor.
**B**: Our algorithms “puts on hold” (or pauses) DFS over search trees that become too large**C**: Note ... | BAC | CAB | ACB | ACB | Selection 2 |
**A**:
The rest of this paper is organized as follows**B**: We provide necessary notation and assumptions in Section II**C**: CPP is introduced and analyzed in Section III. In Section IV, we consider the algorithm B-CPP. Numerical examples are presented in Section V, and we conclude the paper in Section VI. | ACB | ACB | BAC | ABC | Selection 4 |
**A**: We present a new SPP formulation of the PFL problem (1) as the decentralized min-max mixing model**B**: This extends the classical PFL problem to a broader class of problems beyond the classical minimization problem**C**: It furthermore covers various communication topologies and hence goes beyond the centralize... | CBA | ACB | BAC | ABC | Selection 4 |
**A**: To produce robust BRs, entropy maximizing MSs (such as MG(C)CE) have better empirical value and convergence than the uniform MS. For exploration, we can randomly select a valid equilibrium at each iteration which outperforms random joint and random Dirichlet by a significant margin (similar to AlphaStar’s “explo... | BAC | ACB | ABC | CBA | Selection 4 |
**A**: A worst-case approach makes sense for privacy, but for statistical guarantees like generalization, we only need statements that hold with high probability with respect to the sampled dataset, and only on the actual queries issued.**B**: However, its optimality is for worst-case adaptive queries, and the guarante... | BCA | ACB | CBA | BAC | Selection 3 |
**A**: We generate a set of colorings that is guaranteed to contain at least one such coloring**B**:
Using the previous lemmas the problem of finding a reducible single-tree FVC reduces to finding a coloring that properly colors a simple reducible FVC**C**: To generate this set we use the concept of a universal set. | ABC | BAC | CBA | CAB | Selection 2 |
**A**: Inspired by [129], they adapt a pretrained diffusion model to a subject by finetuning on a few reference images of this subject, so that a rare token is associated with this subject**B**: The existing generative image composition methods can be divided into two groups: token-to-object methods and object-to-objec... | ACB | ACB | ACB | BAC | Selection 4 |
**A**: One effective solution to this problem is transfer learning [20], which leverages knowledge from a source domain with abundant data to a target domain with limited data. In our case, this involves transferring knowledge from one city to another. Therefore, we conduct transfer learning experiments on CityNet to d... | BCA | BCA | BAC | CBA | Selection 4 |
**A**: They are evaluated and compared based on some general performance measures**B**: In this and the following section some of the models introduced above are experimentally investigated**C**: Moreover, some general conclusions that can be used in future applications or research are derived.
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**A**: This outcome can be attributed to the limited size of the Pianist8 dataset, comprising only 411 songs. Conversely, in the emotion classification task, MusicBERT demonstrates impressive performance, surpassing our model (70.64%) by a significant margin. This finding is intriguing and suggests that the application... | ACB | CAB | BCA | ABC | Selection 2 |
**A**: This description draws a comparison e.g**B**: to L(k,1)𝐿𝑘1L(k,1)italic_L ( italic_k , 1 )-labeling problem (see e.g**C**: [10] for a survey), where the colors of any two adjacent vertices have to differ by at least k𝑘kitalic_k and the colors of any two vertices within distance 2222 have to be distinct.
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**A**: Moreover, in order to facilitate DeepSC-SR adapting well over various physical channels, a model with strong robustness to channel variations has been investigated. Simulation results demonstrated that DeepSC-SR outperforms the traditional communication systems, especially in the low SNR regime. Hence, our propo... | ABC | CBA | ACB | ACB | Selection 2 |
**A**: For One-Thing-One-Click[48] and MulPro[8], we use the results reported from the MulPro[8] paper**B**: Comparison with existing 3D WSSS methods:
We compare our proposed method with existing 3D WSSS methods[13, 51, 41]**C**: [10] utilizes 2D dense labels on 2D projections of the 3D point clouds and [13] utilize t... | BCA | BCA | BAC | CAB | Selection 3 |
**A**: Table 3:
Monocular 3D object detection results on the KITTI val set for the car category with the evaluation metric of AP40subscriptAP40\rm{AP}_{40}roman_AP start_POSTSUBSCRIPT 40 end_POSTSUBSCRIPT**B**: The results of the previous works are from [9]**C**: Our approach significantly outperforms the previous sta... | CAB | ABC | BAC | BAC | Selection 2 |
**A**: In this example, a text instance appears to be separated in both the text region map and its center line map as the FPN layer fails to build long-range dependency between the text segments in the middle**B**: However, sharing similar visual features sometimes leads to error accumulation**C**: Although the relati... | BAC | ABC | ABC | ACB | Selection 1 |
**A**: Finally, we obtain the first k𝑘kitalic_k most frequently occurring IP addresses in the heap. The complete procedure for finding the first k𝑘kitalic_k of the most frequency IP addresses from host logs is outlined in Algorithm 2.**B**: Then, we continue to perform a round traversal of the memory block to adjust ... | ACB | CBA | CAB | BAC | Selection 2 |
**A**: The work of G. Ju is supported in part by the National Key R & D Program of China (2017YFB1001604). The work of J**B**: Li is partially supported by the National Natural Science Foundation of China No. 11971221 and the Shenzhen Sci-Tech Fund No. RCJC20200714114556020, JCYJ20170818153840322 and JCYJ20190809150413... | CBA | ABC | BAC | BCA | Selection 4 |
**A**: Finally, we have presented experimental results that validate our theory in practice.**B**:
We have introduced TDCD, a communication efficient decentralized algorithm for a multi-tier network model with both horizontally and vertically partitioned data**C**: We have provided a theoretical analysis of the algori... | BAC | ACB | BAC | CAB | Selection 4 |
**A**: The properties of pseudospectra are also discussed, along with a characterization of the pseudospectra for normal matrices. Additionally, for diagonalizable but not necessarily normal matrices, the corresponding Bauer-Fike theorem is presented, which can be found in (trefethen2005spectra, , Theorems 2.2, 2.3, an... | BCA | CBA | ABC | CAB | Selection 1 |
**A**: Motivated by global and local GANs [7], Gated Convolution [36] and Markovian GANs [9], we develop a two-stream discriminator to distinguish genuine images from the generated ones by estimating the feature statistics of both texture and structure. The discriminator is shown in Figure 2 (b)**B**: The texture branc... | ACB | ABC | CBA | CBA | Selection 2 |
**A**: In a binary erasure channel (BEC), a binary symbol is either received correctly or totally erased with probability ε𝜀\varepsilonitalic_ε**B**: Together with the binary symmetric channel (BSC), they are frequently used in coding theory and information theory because they are among the simplest channel models, an... | ABC | ABC | ABC | ACB | Selection 4 |
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