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**A**: Note that row and column operations are effected by left- and right multiplications by transvections**B**:
The key idea is to transform the diagonal matrix with the help of row and column operations into the identity matrix in a way similar to an algorithm to compute the elementary divisors of an integer matrix... | ABC | BCA | BAC | ABC | Selection 3 |
**A**: It is interesting to notice that, although the formulation is based on hybridization, the final numerical solution is defined by a sequence of elliptic problems.**B**:
As in many multiscale methods previously considered, our starting point is the decomposition of the solution space into fine and coarse spaces t... | BAC | BAC | CAB | BAC | Selection 3 |
**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**: These coordinates are computed somehow and their true values can differ from their values stored in the computer**C... | ACB | ABC | BAC | CBA | Selection 2 |
**A**: Single Tweet Model Settings. For the evaluation, we shuffle the 180 selected events and split them into 10 subsets which are used for 10-fold cross-validation (we make sure to include near-balanced folds in our shuffle)**B**: We implement the 3 non-neural network models with Scikit-learn444scikit-learn.org/. Fur... | CBA | BCA | BAC | ABC | Selection 4 |
**A**: The follow-up paper (Gunasekar et al., 2018) studied this same problem with exponential loss instead of squared loss**B**: Unlike the case of squared loss, the result for exponential loss are independent of initialization and with only mild conditions on the step size. Here again, we see the asymptotic nature of... | BCA | CAB | CAB | ACB | Selection 4 |
**A**: For the latter, we select the baselines from state-of-the-art text classification models, i.e., Basic tanh-RNN (madetecting, ), 1-layer GRU-RNN (madetecting, ), 1-layer LSTM (madetecting, ), 2-layer GRU-RNN (madetecting, ), FastText (joulin2016bag, ) and CNN+LSTM (zhou2015c, ) model. The hybrid model CNN+LSTM is... | ACB | ABC | BAC | CBA | Selection 4 |
**A**: In total, our training dataset for AOL consists of 1,740 instances of breaking class and 3,050 instances of anticipated, with over 300 event entities. For GoogleTrends, there are 2,700 and 4,200 instances respectively**B**: Evaluating methodology.
For RQ1, given an event entity e, at time t, we need to classify ... | ABC | BAC | ACB | ACB | Selection 2 |
**A**: Only one of the patients suffers from diabetes type 2 and all are in ICT therapy. In terms of time since being diagnosed with diabetes, patients vary from inexperienced (2 years) to very experienced (35 years), with a mean value of 13.9 years.**B**:
Table 1 shows basic patient information. Half of the patients ... | CBA | BCA | CAB | ACB | Selection 3 |
**A**: To detect salient items in search array stimuli (see Figure 4d), a mechanism that additionally captures low-level feature contrasts might explain the empirical data better. Besides architectural changes, data augmentation in the context of saliency prediction tasks demonstrated its efficiency to improve the robu... | CAB | ACB | BAC | CBA | Selection 1 |
**A**: This definition leads to the general combinatorial question of whether every word has an optimal marking sequence that is block-extending, or whether the seemingly bad choices of marking a symbol that has only isolated occurrences (and that is not the first symbol) is necessary for optimal marking sequences**B**... | CAB | BCA | ACB | BAC | Selection 4 |
**A**: We thank Marc Bellemare and Pablo Castro for their help with Rainbow and Dopamine. The work of Konrad Czechowski, Piotr Kozakowski and Piotr Miłoś was supported by the Polish National Science Center grants UMO-2017/26/E/ST6/00622**B**: The work of Henryk Michalewski was supported by the Polish National Science C... | ABC | CAB | ACB | CAB | Selection 1 |
**A**: The results highlight the superior energy efficiency of the proposed autonomous locomotion mode transition method for negotiating steps of different heights, in contrast to solely depending on the rolling locomotion mode. This underscores the efficiency of the proposed strategy in enabling energy-conscious step ... | ABC | BCA | CBA | ACB | Selection 3 |
**A**: While our work addresses issues similar to [24] and [29], in that trusted advice is related to consistency whereas untrusted advice is related to robustness, it differs in two significant aspects: First, our ideal objective is to identify an optimal
family of algorithms, and we show that in some cases (ski renta... | ACB | ABC | CBA | ACB | Selection 2 |
**A**:
The dataset used in this task had the advantage of being publicly available and played an important role in determining how the use of language is related to the EDD problem**B**: However, it exhibits some limitations from a methodological/clinical point of view**C**: Beyond the potential “noise” introduced by ... | ABC | ACB | BAC | CBA | Selection 1 |
**A**: In the experiments of (Lin et al., 2018), DGC gets far better performance on both accuracy and communication cost than quantization methods**B**: Hence, we do not compare with quantization methods in this paper.
We don’t use the warm-up strategy in the experiments**C**: The momentum coefficient β𝛽\betaitalic_β ... | BAC | CBA | BCA | ABC | Selection 4 |
**A**:
, where ∗*∗ is the convolution333We use convolution instead of cross-correlation only as a matter of compatibility with previous literature and computational frameworks**B**: operation.**C**: Using cross-correlation would produce the same results and would not require flipping the kernels during visualization | ACB | CAB | BCA | CBA | Selection 1 |
**A**: In the next section, we investigate the existing algorithm with its learning rate in large-scale post-disaster scenarios and propose a new algorithm which is more suitable for the UAV ad-hoc network in such scenarios.
**B**: Some algorithms that have been applied in the potential game can also be employed in the... | ABC | CBA | CAB | CAB | Selection 2 |
**A**: This property also hold for the
pyramid side functions, i.e.,formulae-sequence𝑖𝑒i.e.,italic_i **B**: nodal locations), is equal to one**C**: italic_e . , Σn=1Nnϕn(𝐫)=Σn=1Nnψn(𝐫)=1subscript𝑁𝑛𝑛1Σsubscriptitalic-ϕ𝑛𝐫subscript𝑁𝑛𝑛1Σsubscript𝜓𝑛𝐫1\overset{N_{n}}{\underset{n=1}{\Sigma}}\phi_{n}(\textbf... | ACB | ABC | BAC | CBA | Selection 3 |
**A**: The Q-learning algorithm employs a table to estimate the optimal action value function, Q∗superscript𝑄Q^{*}italic_Q start_POSTSUPERSCRIPT ∗ end_POSTSUPERSCRIPT. This table encompasses all states and actions within the environment and utilizes the value function to assess the quality (Q-function) of state-action... | BCA | BAC | ACB | CBA | Selection 4 |
**A**: (2019) by leveraging group normalization (Wu and He, 2018) and leaky ReLU function, redesigned the U-Net architecture in order to make the network more memory efficient for 3D medical image segmentation. Perone et al. (2018) and Bonta and Kiran (2019) designed a dilated convolution neural network with fewer para... | BAC | CAB | ACB | BCA | Selection 2 |
**A**: Independent training fits all networks one after the other and creates an ensemble of networks as a final classifier. Joint training concatenates all tree networks into one single network so that the output layer is connected to all leaf neurons in the second hidden layer from all decision trees and all paramete... | CBA | CAB | ABC | ACB | Selection 2 |
**A**: As is shown subsequently, solving such a subproblem corresponds to one iteration of infinite-dimensional mirror descent (Nemirovsky and Yudin, 1983) or dual averaging (Xiao, 2010), where the action-value function plays the role of the gradient. To encourage exploration, we explicitly incorporate a bonus function... | CAB | BCA | BCA | BAC | Selection 1 |
**A**: (2018a) performed mixed-precision quantization using similar NAS concepts to those used by Liu et al**B**: (2019a) and Cai et al. (2019).
They introduce gates for every layer that determine the number of bits used for quantization, and they perform continuous stochastic optimization of probability parameters ass... | BCA | BAC | CAB | CBA | Selection 1 |
**A**: One main contribution of this paper is establishing a precise relationship (i.e**B**: a filtered homotopy equivalence) between the Vietoris-Rips simplicial filtration of a metric space and a more geometric (or extrinsic) way of assigning a persistence module to a metric space, which consists of first isometrical... | ABC | ACB | CBA | CAB | Selection 1 |
**A**: After investigating similar subclusters with a large density, she learns that t-SNE formed this and more mini-clusters in different areas of the projection as a result of their high (usually identical) similarity.
**B**: By looking at the PCP again (Figure 6(h)), she realizes that these points are all exactly th... | ACB | ABC | BCA | CBA | Selection 4 |
**A**: The first one helps classify the different proposals by their origin of inspiration, whereas the second one provides valuable information about their algorithmic similarities and differences**B**: This double classification allows researchers to identify each new proposal in an adequate context. To the best of o... | BCA | ACB | CAB | CBA | Selection 1 |
**A**: Since a large proportion of clustering methods are based on the graph, it is reasonable to consider how to employ GCN to promote the performance of graph-based clustering methods.
In this paper, we propose an Adaptive Graph Auto-Encoder (AdaGAE) to extend graph auto-encoder into common scenarios**B**: However, t... | BAC | CBA | ACB | CBA | Selection 1 |
**A**: Firewalls, blocking incoming packets on port 53, would as a result generate a similar effect as ingress filtering on our servers: we would not receive any DNS requests to our domain**B**:
DNS technique**C**: However, such a setting does not indicate that the tested network actually performs ingress filtering. | BAC | CAB | CAB | CBA | Selection 1 |
**A**: Before classifying an unlabeled sample, the recurrent pathway processes a sequence of labeled samples from the preceding batches to generate a context representation, which is fed into the skill processing layer. The recurrent layers are modified via backpropagation through time, and, in this manner, the recurre... | BCA | ACB | BCA | BAC | Selection 4 |
**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... | CAB | BAC | CBA | CAB | Selection 2 |
**A**: Finally, we advocate for creating a dataset with ground truth grounding available for 100% of the instances using synthetically generated datasets Kafle et al. (2017); Kafle and Kanan (2017); Kafle et al. (2018); Acharya et al**B**: While our results indicate that current visual grounding based bias mitigation a... | BCA | ACB | BAC | ABC | Selection 3 |
**A**: Sathyendra et al. (2017) presented a dataset and developed a model to automatically identify and label opt-out choices offered in privacy policies. Similarly, Zimmeck et al**B**: (2019) released a set of over 400k URLs to Android app privacy policy pages collected by crawling the Google Play store. Amos et al. (... | ABC | BCA | BAC | BAC | Selection 2 |
**A**: To avoid an asymmetric design and retain a lower complexity level for StackGenVis, we omitted his proposal for the time being, but we consider implementing both methods in the future.**B**: Another positive opinion from E3 was that, with a few adaptations to the performance metrics, StackGenVis could work with r... | BCA | CBA | CAB | BCA | Selection 3 |
**A**: Model-Agnostic Meta-Learning (MAML) [Finn et al., 2017] is one of the most popular meta-learning methods**B**: It is trained on plenty of tasks (i.e**C**: 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 successfu... | CAB | BAC | ACB | ABC | Selection 4 |
**A**: In particular, each UAV is equipped with a cylindrical conformal array (CCA), and a novel-codebook-based mmWave beam tracking scheme is proposed for such a highly dynamic UAV network. More specifically, the codebook consists of the codewords corresponding to various subarray patterns and beam patterns**B**: Base... | BAC | BCA | BAC | CAB | Selection 2 |
**A**: This will be bootstrapped to the multi-color case in later sections**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 no... | ABC | CBA | BCA | ACB | Selection 1 |
**A**: In §6.1, we introduce Q-learning and its mean-field limit**B**: In §6.2, we establish the global optimality and convergence of Q-learning. In §6.3, we further extend our analysis to soft Q-learning, which is equivalent to policy gradient.
**C**: In this section, we extend our analysis of TD to Q-learning and pol... | ACB | CAB | BCA | ACB | Selection 3 |
**A**: (2017); Aharoni et al. (2019)**B**: Model capacity has been found crucial for massively multilingual NMT to support language pairs with varying typological characteristics Zhang et al. (2020); Xu et al. (2021a). Using model layers efficiently with depth-wise LSTMs is likely to benefit multilingual NMT.
**C**: Mu... | CBA | BAC | BCA | ABC | Selection 3 |
**A**: italic_ε start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT ( italic_x ) ∧ italic_ε start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT ( italic_x ) ∧ ¬ ( italic_x = italic_y ) for i∈I𝑖𝐼i\in Iitalic_i ∈ italic_I and θi,j≜∃x.∃y.εi(x)∧εj(x)formulae-sequence≜subscript𝜃𝑖𝑗𝑥𝑦subscript𝜀𝑖𝑥subscript𝜀𝑗𝑥\theta_{i,j}\... | ABC | ABC | CAB | CBA | Selection 4 |
**A**:
Relationship to Distortion Distribution: We first emphasize the relationship between two learning representations and the realistic distortion distribution of a distorted image. In detail, we train a learning model to estimate the distortion parameters and the ordinal distortions separately, and the errors of e... | ACB | BCA | BAC | BAC | Selection 1 |
**A**: SNGM achieves the best performance for almost all batch size settings.**B**: 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**C**: We don’t use training tricks such as warm-up [7] | CBA | BAC | CAB | ABC | Selection 1 |
**A**: In Section 5, we describe a 9-approximation algorithm for an inhomogeneous MatSup problem, which is an extension of results in [13] and [3] (specifically, our method in Algorithm 6 involves an iterative rounding approach similar to that of [13])**B**:
We follow up with 3333-approximations for the homogeneous ro... | BCA | BAC | CAB | ACB | Selection 2 |
**A**: Further, the estimations of these rates are substituted into the recursive inequality of the conditional mean square error between the states and the global optimal solution. Finally, by properly choosing the step sizes, we prove that the states of all local optimizers converge to the same global optimal solutio... | CAB | CBA | ACB | CBA | Selection 1 |
**A**: Differential privacy [6, 38], which is proposed for query-response systems, prevents the adversary from inferring the presence or absence of any individual in the database by adding random noise (e.g., Laplace Mechanism [7] and Exponential Mechanism [24]) to aggregated results**B**: However, differential privacy... | ABC | ACB | BAC | ACB | Selection 1 |
**A**: In addition to models listed in Table 3, another PointRend with slightly different setting (stacking two BFP modules, and increasing the RoIAlign size from original 7 to 10 for bounding box branch) is trained and achieves 76.95 mAP on testing set. So, there are 5 models used for final ensemble.
**B**: Note that ... | CBA | ABC | ACB | ABC | Selection 1 |
**A**: More specifically, we proved**B**:
In version 1 of this note, which can still be found on the ArXiv, we showed that the analogous version of the conjecture for complex functions on {−1,1}nsuperscript11𝑛\{-1,1\}^{n}{ - 1 , 1 } start_POSTSUPERSCRIPT italic_n end_POSTSUPERSCRIPT which have modulus 1111 fails**C**... | CBA | ABC | CAB | CBA | Selection 3 |
**A**: In this section, we perform empirical experiments on synthetic datasets to illustrate the effectiveness of LSVI-UCB-Restart and Ada-LSVI-UCB-Restart**B**: We compare the cumulative rewards of the proposed algorithms with five baseline algorithms: Epsilon-Greedy (Watkins, 1989), Random-Exploration, LSVI-UCB (Jin ... | ACB | ABC | CAB | ACB | Selection 2 |
**A**: For dissemination, various channels were employed including a mailing list of students from a local Singapore university, an informal Telegram supergroup joined by students, alumni, and faculty of the same university, and personal contacts of the researchers. Further spreading of the survey by participants was e... | ABC | CBA | BCA | BCA | Selection 2 |
**A**:
We conduct an analysis of the training time for decentRL and AliNet with varying hidden-sizes on a V100 GPU, as detailed in Table 12**B**: The two methods exhibit comparable running times per epoch. AliNet runs marginally faster than decentRL with smaller hidden sizes, but the total training time of decentRL is... | CAB | ACB | ABC | BAC | Selection 2 |
**A**: According to a resent research in model-based RL [48], the ensemble model with probabilistic neural networks achieves the state-of-the-art performance in model-based planning. Each probabilistic network outputs a Gaussian distribution with diagonal covariances, and an ensemble of probabilistic networks captures ... | ACB | CAB | CAB | BCA | Selection 4 |
**A**: However, Floater-Hormann becomes indistinguishable from 5thsuperscript5𝑡ℎ5^{th}5 start_POSTSUPERSCRIPT italic_t italic_h end_POSTSUPERSCRIPT-order splines.
Further, when considering the amount of coefficients/nodes required to determine the interpolant, plotted in the right panel (with logarithmic scales on bo... | CAB | CBA | ABC | BAC | Selection 4 |
**A**: The key observation that we make is that the DR learning problem can be cast as a style transfer task [DBLP:conf/cvpr/GatysEB16], thus allowing us to borrow techniques from this extensively explored area.
**B**: The framework is general and can utilize any DGM**C**: Furthermore, even though it involves two stage... | BAC | CBA | CAB | ABC | Selection 3 |
**A**: To simulate the aforementioned structural computer theory, a device in the form of a USB connection**B**: We decided to verify that the structural computer theory presented so far is actually working without the cost of circuit building, to simulate the connection of complex Circuits rather than just Gate Circui... | ACB | BCA | ABC | BCA | Selection 1 |
**A**: Some well-studied families of polynomials include the Dickson polynomials and reverse Dickson polynomials, to name a few**B**: Conditions for such families of maps to define a permutation of the field 𝔽𝔽\mathbb{F}blackboard_F are well studied and established for special classes like Dickson polynomials [20], l... | BAC | ABC | BCA | BAC | Selection 3 |
**A**: For example, one may wish to make decisions on which views to measure in the future based on the set of views selected using the current data.**B**: Although sparser models are typically considered more interpretable, a researcher may be interested in interpreting not only the model and its coefficients, but als... | CBA | CAB | CAB | ABC | Selection 1 |
**A**: Feature selection methods fall into three categories, wrapper, filter and embedded methods [30]**B**: However, filter feature selection is preferred due to its high efficiency and independence of prediction models.
**C**: Conceptually, methods from the three categories can all be utilized for relevant variable s... | BAC | ABC | ACB | CAB | Selection 3 |
**A**: [2020] Faury et al**B**: [2020] use a bonus term for optimization in each round, and their algorithm performs non-trivial projections on the admissible log-odds. While we do reuse the Bernstein-style concentration inequality as proposed by them, their results do not seem to extend directly to the MNL setting wit... | BCA | CBA | ABC | CAB | Selection 1 |
**A**: a) Distribution of action duration in ActivityNet-v1.3 [7]**B**: Actions are divided into five duration groups (in seconds): XS (0, 30], S (30, 60], M (60, 120], L (120, 180], and XL (180, inf). b) TAL Performance of different methods on actions of different duration.**C**:
Figure 1: Short actions are the majo... | ACB | CBA | CAB | BCA | Selection 4 |
**A**:
ATMSeer [WMJ∗19] implements a multi-granularity visualization for model selection and hyperparameter tuning**B**: It is a visualization tool coupled with a backend framework, called ATM [SDC∗17], that allows the users to interact with the middle steps of an AutoML process and control them by adjusting the searc... | CAB | BCA | ABC | ACB | Selection 3 |
**A**: In [29], previous works are extended to solve the consensus problem on networks under limited and unreliable information exchange with dynamically changing interaction topologies. The convergence of the algorithm is provided under the ultimately connected assumption.
Another consensus protocol is introduced in [... | BAC | BCA | CBA | BAC | Selection 3 |
**A**: Although this way there is no bias, in general the resulting correspondences are not cycle-consistent**B**: As such, matching shape A via shape B to shape C, may lead to a different correspondence than matching shape A directly to C.
**C**: Alternatively, one could solve pairwise shape matching problems between ... | ABC | CAB | CAB | BCA | Selection 4 |
**A**: Rooted path graphs can be recognized in linear time by using the algorithm by Dietz [7]. All inclusions between introduced classes of graphs are resumed in the following:**B**:
We now introduce a last class of intersection graphs**C**: A rooted path graph is the intersection graph of directed paths in a rooted ... | ABC | BAC | CAB | BAC | 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... | BCA | CBA | ACB | ABC | Selection 1 |
**A**: 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 transport first solves the variation... | BCA | BCA | CAB | ACB | Selection 3 |
**A**: A standard 4-way intersection is shown in Fig. 2, which consists of four approaches, i.e., "east", "south", "west" and "north"**B**: For an intersection, the incoming lanes refer to the lanes where the vehicles are about to enter the intersection. In real world, most intersections are equipped with 4-way enterin... | CBA | ACB | BAC | ABC | Selection 3 |
**A**: In contrast, almost all known online bin packing algorithms are analyzed using a weighting technique (?), which treats each bin “individually” and independently from the others (by assigning weights to items and independently comparing a bin’s weight in the online algorithm and the optimal offline solution)**B**... | CAB | CAB | CBA | BCA | Selection 4 |
**A**: Throughout all experiments, we train models with Chamfer distance. We also set λ=0.0001𝜆0.0001\lambda=0.0001italic_λ = 0.0001. We denote LoCondA-HC when HyperCloud is used as the autoencoder architecture (Part A in Fig. 1) and LoCondA-HF for the HyperFlow version.
**B**: In this section, we describe the experim... | ACB | ABC | CAB | ACB | Selection 3 |
**A**: It remains to understand what the solution even looks like. Considering the global objective function, we have:
**B**: The previous lemma gives us an understanding of how quickly we can approximate the solution**C**: In particular, in coordinates that can be non-zero we are able to have a value that absolutely c... | CBA | ACB | BAC | CAB | Selection 4 |
**A**: In this section we present some experimental results to reinforce
Conjecture 14**B**: In the first part, we focus on the complete analysis of small graphs, that is: graphs of at most 9 nodes. In the second part, we analyze larger families of graphs by random sampling instances.**C**: We proceed by trying to find... | CAB | ABC | CAB | ACB | Selection 4 |
**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... | BAC | ABC | CAB | CBA | Selection 3 |
**A**: Although this idea appears valuable and straightforward for binary classification problems, it will not scale well with multiclass problems addressed by our VA system. It will be tough to present confusion between classes when more than a couple of class labels are available, which is typical in multiclass probl... | CBA | BAC | CAB | BAC | 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... | ACB | ABC | CAB | CAB | Selection 2 |
**A**: For Biased MNISTv1, we use a convolutional neural network with four ReLU layers consisting of a max pooling layer attached after the first convolutional layer. For GQA-OOD, we employ the UpDn architecture [4], which is widely used for VQA [58, 36, 66].**B**: For CelebA, we use ResNet-18 [29]**C**:
For each data... | CBA | BAC | BCA | BCA | Selection 1 |
**A**: We also convert the two definitions with post-processing methods following Sec. 4.2.2.
We respectively conduct benchmarks for 2D PoG and 3D gaze estimation**B**: We mark the top three performance in all benchmarks with underlines.**C**: The 3D gaze estimation also are divided into within-dataset and cross-datase... | CBA | CAB | BCA | ACB | Selection 4 |
**A**: The obtained high accuracy compared to other face recognizers is achieved due to the best features extracted from the last convolutional layers of the pre-trained models, and the high efficiency of the proposed BoF paradigm that gives a lightweight and more discriminative power comparing to classical CNN with so... | ACB | BAC | CAB | CBA | Selection 1 |
**A**: Then, at a high level, quicksort is a size-preserving definition with the input list length as its termination measure**B**:
That is, we assume that we have definitions that (1) append two lists together and (2) partitions one by a pivot**C**: For brevity, we nest patterns (boxed and highlighted yellow), which ... | ABC | CAB | BCA | BAC | Selection 4 |
**A**: First, to achieve data protection and access control, we adopt the lifted-ElGamal based PRE scheme, as discussed in [16, 17, 18, 19, 20], whose most prominent characteristic is that it satisfies the property of additive homomorphism**B**: Then this homomorphism property is fully exploited to facilitate the integ... | CBA | BCA | ACB | CBA | Selection 2 |
**A**: Modeling feature interactions is a crucial aspect of predictive analytics and has been widely studied in the literature. FM Rendle (2010) is a popular method that learns pairwise feature interactions through vector inner products**B**: (2017), which considers the weight of different second-order feature interact... | ACB | BCA | BCA | BCA | Selection 1 |
**A**: [2019] but already implicitly used earlier in Lacoste-Julien & Jaggi [2015] as:
**B**: We can make use of the proof of convergence in primal gap to prove linear convergence in Frank-Wolfe gap**C**: In order to do so, we recall a quantity formally defined in Kerdreux et al | BCA | ACB | CAB | BCA | Selection 3 |
**A**: The input contains a graph G𝐺Gitalic_G and an approximation parameter ε𝜀\varepsilonitalic_ε.**B**:
In this section we describe how to generalize our algorithm to other computation models**C**: We begin by describing what procedures our framework requires the access to | BCA | CAB | CBA | BAC | Selection 2 |
**A**: To the best of our knowledge, CPP is the first method that enjoys linear convergence under such a general setting.**B**:
We propose CPP – a novel decentralized optimization method with communication compression**C**: The method works under a general class of compression operators and is shown to achieve linear ... | CBA | CBA | ACB | CAB | Selection 4 |
**A**: As mentioned in examples above, saddle point problems often arise as an auxiliary tool for the minimization problem. It turns out that if we have a personalized minimization problem, and then for some reason (for example, to simplify the process of the solution or to make the learning more stable and robust) rew... | BAC | CAB | ACB | ACB | Selection 2 |
**A**: A gap, ΔΔ\Deltaroman_Δ, of zero implies convergence to an equilibrium. We also measure the expected value obtained by each player, because convergence to an equilibrium does not imply a high value. Both gap and value metrics need to be evaluated under a meta-distribution. Using the same distribution as the MS ma... | ACB | ACB | BAC | BCA | Selection 4 |
**A**: One natural way to enforce differential privacy is by directly adding noise to the results of a numeric-valued query, where the noise is calibrated to the global sensitivity of the function to be computed—the maximal change in its value between any two neighboring datasets. Dwork et al**B**: Differential privacy... | CAB | ABC | CBA | BAC | Selection 4 |
**A**:
Our algorithmic results are based on a combination of graph reduction and color coding [6] (more precisely, its derandomization via the notion of universal sets)**B**: After such reduction steps, the size of the entire structure we are trying to find can be bounded in terms of the parameter k𝑘kitalic_k. We the... | BCA | ACB | ABC | BAC | Selection 2 |
**A**: To overcome this problem, painterly image harmonization [104] has been studied to harmonize the realistic foreground according to the artistic background to obtain a uniformly stylized composite image.
**B**: There exist certain application scenarios that the background is an artistic image while the foreground ... | ABC | ACB | CBA | ACB | Selection 3 |
**A**:
Inter-city correlations**B**: Our results demonstrate that transfer learning leads to error reductions in all source-target pairs, as compared to using target data only**C**: Notably, the largest reduction of approximately 15% is observed in the case of Shenzhen and Chongqing. These findings suggest that there ... | BCA | ABC | CBA | CBA | Selection 2 |
**A**: In the experiments only the predictive power is considered**B**: The benefit of working with models that are built upon or include a point predictor is that one also gets a direct estimate of the response variable. Since this is important in many situations, the R2superscript𝑅2R^{2}italic_R start_POSTSUPERSCRIP... | CBA | BAC | ACB | BCA | Selection 4 |
**A**: For the sequence-level tasks, which require only a prediction for an entire sequence, we follow \textciteemopia and choose the Bi-LSTM-Attn model from \textcitelin2017structured as our baseline, which was originally proposed for sentiment classification in NLP.
The model combines LSTM with a self-attention modul... | BCA | BAC | CBA | ABC | Selection 4 |
**A**: [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.
**B**: to L(k,1)𝐿𝑘1L(k,1)italic_L ( italic_k , 1 )-labeling problem (see e.g**C**: This description draws a comparison e.g | CAB | CBA | ABC | BCA | Selection 2 |
**A**: The mechanism behind this is that semantic information takes into account the meaning and veracity of source data because they can be both informative and factual[7], besides, the semantic data can be compressed to a proper size by employing a lossless method[8]. However, it is very challenging to define the sem... | CBA | BCA | ACB | ACB | Selection 1 |
**A**: The baseline method means the basic segmentation network trained with only the weak labels and without CSFR and ISFR modules.
**B**: KPConv(paper) is taken from the paper-reported score, and KPConv(retrain) is the score from our basic segmentation network trained with 100% labels**C**: TABLE V: The class-specifi... | CBA | BAC | BCA | BAC | Selection 1 |
**A**: There are several recent methods considering utilizing the geometric information for monocular 3D object detection [15, 31, 29, 5, 19].
One research direction mainly focuses on using geometry information to improve the detection performance in the inference stage via post-processing [3, 39]**B**: UR3D [39] uses ... | BCA | CBA | CAB | ACB | Selection 4 |
**A**: This explains why the overall performance is often further improved when both FPNS (Node) and FPNS (GGTR) are applied. The performance improvements reflect that our FPNS strategies can suppress false detections while not overly affecting true detections.
**B**: FPNS (Node) rectifies false detections by measuring... | ABC | ABC | CAB | ABC | Selection 3 |
**A**:
The collection of the statistics of large-scale IP address data is one of the most fundamental problems in network traffic measurement**B**: In this paper, we addressed this problem**C**: Specifically, the two proposed methods present two different relationship mapping mechanisms between memory blocks and IP ad... | BCA | CAB | CAB | ABC | Selection 4 |
**A**: Generalizations to n𝑛nitalic_n-tuple cases are provided in Section 5. In Section 6, numerical experiments for a 3-field formulation of the Biot model are provided to justify the advantages of using positively stable preconditioners. Finally, concluding remarks are given in Section 7.
**B**: The outline of the r... | CAB | CBA | ACB | ACB | Selection 1 |
**A**: Federated averaging methods have been studied in the context of convex objectives (Stich, 2019; Wang et al., 2019; Khaled et al., 2020) and non-convex objectives (Yu et al., 2019; Haddadpour and Mahdavi, 2019; Li et al., 2020; Wang and Joshi, 2021).
The common approach is to take multiple (stochastic) gradient s... | ACB | BCA | ABC | CAB | Selection 2 |
**A**: Kilmer2008third introduced a novel form of tensor multiplication that enables the representation of a third-order tensor as a product of other third-order tensors**B**: The multiplication of tensors, a fundamental and crucial operation analogous to matrix multiplication, has garnered considerable attention acro... | CBA | ACB | BAC | ABC | Selection 3 |
**A**: The Bi-GFF module is developed to enhance the consistency of the rebuilt structures and textures**B**: For the results obtained using a simpler fusion module (a channel-wise concatenation followed by a convolution layer), blurred edges and unexpected noise can be observed in Figure 7 (d), especially around compl... | ABC | BAC | CAB | BCA | Selection 4 |
**A**: The concept of BEC was first introduced by Elias in 1955 InfThe **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, and many problems in communication theory can be reduced to problems in a B... | CAB | BCA | ACB | CAB | Selection 2 |
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