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**A**: This is done in Magma [14] using the results of Elliot Costi [6] and in GAP using the results of this paper see Section 6**B**: One important task in this context is writing elements of classical groups as words in standard generators using SLPs**C**: Other rewriting algorithms also exist, for example Cohen et a... | BAC | ACB | ACB | ABC | Selection 1 |
**A**: The exact definition of some basis functions requires solving global problems, but, based on decaying properties, only local computations are required, although these are not restricted to a single element**B**: It is interesting to notice that, although the formulation is based on hybridization, the final numer... | ABC | ACB | BCA | CBA | Selection 3 |
**A**: Alg-CM uses an involved subroutine (far more complicated than ours given in Algorithm 1) to update the coordinates in each iteration, which accumulates the inaccuracy of coordinates. Even worse, this subroutine computes three angles and selects the smallest to decide how to proceed each time, and due to float is... | BCA | ABC | CBA | BAC | Selection 3 |
**A**: Early in an event, the related tweet volume is scanty and there are no clear propagation pattern yet. For the credibility model we, therefore, leverage the signals derived from tweet contents**B**: Thus, a mechanism for carefully considering the ‘vote’ for individual tweets is required. In this work, we overcome... | ACB | BAC | CAB | ABC | Selection 1 |
**A**: We might improve the validation and test errors even when when the decrease in the training loss is tiny and even when the validation loss itself increases.
**B**: Instead, we should look at the 00–1111 error on the validation dataset**C**: We should not rely on plateauing of the training loss or on the loss (lo... | CAB | CBA | BAC | ABC | Selection 2 |
**A**: . As shown in Table 11, CreditScore is the best feature in general. Figure 10 shows the result of models learned with the full feature set with and without CreditScore**B**: Overall, adding CreditScore improves the performance, significantly for the first 8-10 hours. The performance of all-but-CreditScore jiggle... | CBA | ACB | ABC | ACB | Selection 3 |
**A**: The accuracy for basic majority vote is high for imbalanced classes, yet it is lower at weighted F1. Our learned model achieves marginally better result at F1 metric.**B**:
Results**C**: The baseline and the best results of our 1stsuperscript1𝑠𝑡1^{st}1 start_POSTSUPERSCRIPT italic_s italic_t end_POSTSUPERSCR... | BAC | ACB | CAB | ABC | Selection 3 |
**A**: 3 times the average insulin dose of others in the morning.**B**: The insulin intakes tend to be more in the evening, when basal insulin is used by most of the patients**C**: The only difference happens to patient 10 and 12 whose intakes are earlier at day.
Further, patient 12 takse approx | BAC | BCA | CBA | CAB | Selection 4 |
**A**: Entries between the second and the third line are models based on theoretical considerations and define a baseline rather than competitive performance. Arrows indicate whether the metrics assess similarity **B**: The first line separates deep learning approaches with architectures pre-trained on image classifica... | CBA | CAB | ACB | ACB | Selection 1 |
**A**: In this context, our negative result of Section 5.1 can also be interpreted as a series of unconditional results which state that multiple natural greedy strategies for computing the locality number (and their equivalents for computing the cutwidth) do not provide low-ratio approximations of MinLoc (or MinCutwid... | BAC | CAB | ABC | ABC | Selection 2 |
**A**: Applications of such approaches to both high-fidelity simulated environments and real-world data represent an exciting direction for future work that can enable highly efficient learning of behaviors from raw sensory inputs in domains such as robotics and autonomous driving.**B**: As a long-term challenge, we be... | CBA | BAC | ABC | BCA | Selection 1 |
**A**:
The implementation of the energy criterion strategy has proven effective in facilitating autonomous locomotion mode transitions for the Cricket robot when negotiating steps of varying heights**B**: A significant feature of this method is the determination of transition criterion threshold values based on studie... | CAB | CAB | ACB | BAC | Selection 3 |
**A**: For a very simple example, consider the well-known ski rental problem: this is a simple, yet fundamental resource allocation, in which we have to decide ahead of time whether to rent or buy equipment without knowing the time horizon in advance. In the traditional advice model, one bit suffices to be optimal: 0 f... | BAC | CBA | CAB | CAB | Selection 2 |
**A**: The interested readers could see the relation between the green/positive curve there and the color intensity of each writing shown in 9(a)..
In this example, we show in (a) a painted piece of the subject’s writings history that the system users could use to identify which were the writings involved, and to what ... | CBA | CAB | BAC | BAC | Selection 2 |
**A**: We eliminate the assumption of ring-allreduce compatibility from (Xu and Huang, 2022) and only assume that the compressor has the δ𝛿\deltaitalic_δ-approximate property. This makes our convergence analysis for GMC+ applicable to a broader range of compressors, such as top-s𝑠sitalic_s, which is not ring-allreduc... | BAC | BAC | BAC | CBA | Selection 4 |
**A**: Using cross-correlation would produce the same results and would not require flipping the kernels during visualization**B**: operation.**C**:
, where ∗*∗ is the convolution333We use convolution instead of cross-correlation only as a matter of compatibility with previous literature and computational frameworks | ACB | ABC | BAC | BCA | Selection 4 |
**A**:
Game theory provides an efficient tool for the cooperation through resource allocation and sharing [20][21]. A computation offloading game has been designed in order to balance the UAV’s tradeoff between execution time and energy consumption [25]**B**: applied the Bayesian game-theoretic methodology in UAV’s in... | CBA | CBA | ACB | CAB | Selection 3 |
**A**: Similarly,**B**: are obtained using FEMM models**C**: For the FEMM model used to find ψmainsubscript𝜓𝑚𝑎𝑖𝑛\psi_{main}italic_ψ start_POSTSUBSCRIPT italic_m italic_a italic_i italic_n end_POSTSUBSCRIPT,
the dc current in the main coil was set to Imain=subscript𝐼𝑚𝑎𝑖𝑛absentI_{main}=italic_I start_POST... | CAB | BCA | BAC | BCA | Selection 1 |
**A**: The majority of analytical and empirical studies suggest that overestimation typically stems from the max operator used in the Q-learning value function**B**: This phenomenon introduces a positive bias that may lead to asymptotically sub-optimal policies, distorting the cumulative rewards**C**: Additionally, the... | BAC | BCA | ABC | BCA | Selection 1 |
**A**: Figure 1 indicates the categories we cover in this review, along with a timeline of the most influential papers in the respective categories**B**: Moreover, Figure 2 shows a high-level overview of the deep semantic segmentation pipeline, and where each of the categories mentioned in Figure 1 belong in the pipeli... | BCA | BAC | BAC | BAC | Selection 1 |
**A**: (2020) analyze the performance across different dataset sizes.
Olson et al. (2018) evaluate the performance of modern neural networks using the same test strategy as Fernández-Delgado et al. (2014) and find that neural networks achieve good results but are not as strong as random forests.**B**: (2017) demonstrat... | ACB | BAC | CBA | CAB | Selection 3 |
**A**: Such a notion of robustness partially justifies the empirical advantages of KL-regularized policy optimization (Neu et al., 2017; Geist et al., 2019). To the best of our knowledge, OPPO is the first provably sample-efficient policy optimization algorithm that incorporates exploration.
**B**: In comparison, exist... | BCA | ACB | CBA | ACB | Selection 3 |
**A**:
However, training such discrete-valued DNNs555Due to finite precision of computer arithmetic, in fact any DNN is discrete-valued**B**: However, we use this term here to emphasize the extremely small number of values**C**: is difficult as they cannot be directly optimized using gradient-based methods. | CAB | ABC | CBA | CBA | Selection 2 |
**A**: the spaces admit locally finite partition of unity subordinate to the covers), whereas in our version that condition is automatically satisfied since we only consider paracompact spaces. Our proof technique differs from that of [81] in that whereas [81] relies on a result from [30], our proof follows the traditi... | BAC | ABC | CBA | BAC | Selection 3 |
**A**: There is no restriction, however, to having labels when using t-viSNE; one might use the results of a clustering algorithm, for example, as a replacement for pre-defined labels, or simply no labels at all**B**: Apart from not having any specific color mapping in the overview and the PCP, none of the other techni... | ACB | BCA | CAB | ABC | Selection 2 |
**A**: Sometimes, the movement of the animal also obeys to food search and retrieval. In this case, we consider that the algorithm belongs to the foraging inspiration type, rather than to the movement type. Nowadays, inspiration by foraging mechanisms is becoming more and more consolidated in the research community, ap... | CBA | BCA | CAB | BCA | Selection 1 |
**A**: How to design a graph convolution operator is a key issue and has attracted a mass of attention**B**: Most of them can be classified into 2 categories, spectral methods [24] and spatial methods[25].**C**:
In recent years, GCNs have been studied a lot to extend neural networks to graph type data | ACB | ABC | ACB | BCA | Selection 4 |
**A**:
Path Maximum Transmission Unit Discovery (PMTUD) determines the MTU size on the network path between two IP hosts**B**: The process starts by setting the Don’t Fragment (DF) bit in IP headers**C**: Any router along the path whose MTU is smaller than the packet will drop the packet, and send back an ICMP Fragmen... | ABC | CBA | BAC | BAC | Selection 1 |
**A**:
The context pathway is based on a recurrent neural network (RNN) approach**B**: The alternative was to use a long-short term memory (LSTM), which employs gating variables to better remember information in long sequences [28]. However, in preliminary experiments LSTM did not improve generalization accuracy signi... | CBA | ACB | CAB | BCA | Selection 2 |
**A**: The version for automaton semigroups does not follow directly from 8, as the free monogenic semigroup is not a complete automaton semigroup [4, Proposition 4.3] or even a (partial) automaton semigroup (see [8, Theorem 18] or [20, Theorem 1.2.1.4]).
**B**: The construction used to prove Theorem 6 can also be used... | CBA | BCA | CAB | BAC | Selection 3 |
**A**: The VQA-CP dataset Agrawal et al. (2018) was introduced to study the robustness of VQA methods against linguistic biases**B**: Since it contains different answer distributions in the train and test sets, VQA-CP makes it nearly impossible for the models that rely upon linguistic correlations to perform well on th... | BAC | BAC | BCA | CBA | Selection 3 |
**A**: While Wilson et al**B**: (2016) followed a bottom-up approach and identified different categories from analysis of data practices in privacy policies, we followed a top-down approach and applied topic modelling to the corpus in order to extract common themes for paragraphs. The categories identified in the OPP-1... | CAB | CAB | CBA | BCA | Selection 4 |
**A**: However, the utilization of user-selected weights for multiple validation metrics is one way towards interpreting and trusting the results of stacking ensembles**B**: This is an advantage identified by E2. In the first use case we presented to him, he noted that: “if you are interested in the fairness of the res... | CBA | CAB | BCA | BAC | Selection 3 |
**A**: In Weibo, FewRel and Amazon, the settings are 500/1000/1500-shot, 3/4/5-shot and 3/4/5-shot respectively (Table 2).
When the data quantity is small, the advantage of MAML is more significant. In Persona, the C Score and BLEU of MAML outperform baselines on 50-shot and 100-shot settings, but on 120-shot setting, ... | CBA | BCA | BCA | BAC | Selection 4 |
**A**: Serving as a reference, the minimum-beamwidth scheme always select the minimum beamwidth, i.e., the maximum number of antenna elements for an activated subarray. To evaluate the performance of the proposed two-step scheme, the exhaustive searching scheme for the optimal layer index is also simulated as a compari... | CAB | BCA | BAC | BAC | Selection 2 |
**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 | BAC | CBA | Selection 4 |
**A**: On the other hand, when the value function approximator in TD is an overparameterized multi-layer neural network, which is required to be properly scaled, such a feature representation stabilizes at the initial one (Cai et al., 2019), making the explicit local linearization in nonlinear gradient TD unnecessary. ... | BAC | ABC | CAB | ABC | Selection 3 |
**A**: Yu et al. (2018) suggest that skip connections are “shallow” themselves, and only fuse by simple, one-step operations, and therefore Yu et al. (2018) augment standard architectures with deeper aggregation to better fuse information across layers to improve recognition and resolution**B**: (2018) propose a multi-... | BAC | BCA | ACB | CAB | Selection 3 |
**A**: \prime},y^{\prime})}\subseteq f^{-1}(U)( italic_a start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT , italic_y start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT ) ∈ italic_V start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT start_POSTSUPERSCRIPT ( italic_a start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT , italic_y start_POSTSUPERSCRIPT ′... | BAC | CBA | BCA | ABC | Selection 4 |
**A**: As illustrated in Fig. 6, the distortion parameter estimation achieves the lowest error (0.15) using InceptionV3 as the backbone under 80% training data, which indicates its performance requires more complicated and high-level features extracted by deep networks**B**: With the explicit relationship to image feat... | ACB | ACB | ACB | BCA | Selection 4 |
**A**: Furthermore, it achieves faster convergence rates than LARS for the small and large batch sizes, which is consistent with our convergence analysis for the block-wise update strategy.**B**: We can observe that in the small-batch training, SNGM and other large-batch training methods achieve similar performance in ... | CBA | BAC | ACB | ABC | Selection 1 |
**A**: First, we develop algorithms for the simpler polynomial-scenarios model. Second, we sample a small number of scenarios from the black-box oracle and use our polynomial-scenarios algorithms to (approximately) solve the problems on them**B**: Finally, we extrapolate the solution to the original black-box problem. ... | BCA | BAC | ABC | ACB | Selection 1 |
**A**: In [11], the local gradient noises are independent with bounded second-order moments and the graph sequence is i.i.d.
In [12]-[14], the (sub)gradient measurement noises are martingale difference sequences and their second-order conditional moments depend on the states of the local optimizers**B**: The random gra... | BCA | ACB | CAB | CAB | Selection 1 |
**A**: It is mainly because the number of tuples in each group increases with the growth of l𝑙litalic_l**B**:
Results from Figure 10 show that the increase of l𝑙litalic_l lowers the information loss but raises the relative error rate**C**: On the one hand, in random output tables, the probabilities that tuples have ... | BCA | ACB | BAC | ACB | Selection 3 |
**A**: It can be seen that PointRend generates much finer and smoother segmentation boundaries than HTC and SOLOv2, it also handles overlapped instances gradely (see top-left corner in Figure 2)**B**: Meanwhile, PointRend succeeds in distinguishing holes inside objects as background while HTC and SOLOv2 may predict inc... | BCA | CBA | CAB | ACB | Selection 1 |
**A**:
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**B**: More specifically, we proved**C**... | ACB | CAB | ABC | ABC | Selection 1 |
**A**:
In this section, we describe our proposed algorithm LSVI-UCB-Restart, and discuss how to tune the hyper-parameters for cases when local variation is known or unknown**B**: For both cases, we present their respective regret bounds**C**: Detailed proofs are deferred to Appendix B. Note that our algorithms are all... | ABC | BAC | BCA | BCA | Selection 1 |
**A**: As a measure against fake news, the Protection from Online Falsehoods and Manipulation Act (POFMA) was passed on May 8, 2019, to empower the Singapore Government to more directly address falsehoods that hurt the public interest**B**: Singapore is a city-state with an open economy and diverse population that shap... | BAC | ACB | BCA | BCA | Selection 1 |
**A**: The existing inductive KG embedding methods, such as LAN [21], are unsuitable for adaptation to this task as they are tailored for entity prediction.**B**:
Although GCN and GAT are generally regarded as inductive models for graph representation learning, our analysis in previous sections suggests their limited ... | CAB | BAC | ACB | ACB | Selection 1 |
**A**: In this section, we discuss the basic latent-variable models, i.e., variational auto-encoder (VAE), and applying Conditional VAE (CVAE) in modeling the multimodality and stochasticity of dynamics**B**:
One may curious about whether other variational models can be used in exploration**C**: Considering a typical ... | ABC | ACB | ACB | BAC | Selection 4 |
**A**: That is: For given arbitrary nodes P𝑃Pitalic_P, determine the polynomial space ΠΠ\Piroman_Π such that
P𝑃Pitalic_P is unisolvent with respect to ΠΠ\Piroman_Π**B**: We complement the established notion of unisolvent nodes by the dual notion of unisolvence**C**: In doing so, we revisit earlier results by Carl de ... | ACB | CBA | ABC | BAC | Selection 4 |
**A**: They aren’t really separating into nuisance and independent only.. they are also throwing away nuisance.**B**: Prior work in unsupervised DR learning suggests the objective of learning statistically independent factors of the latent space as means to obtain DR. The underlying assumption is that the latent variab... | CBA | BAC | CAB | CBA | Selection 3 |
**A**: Thus, signal cables require one transistor for switching action at the end**B**: If a pair of lines of the same color is connected, 1, if broken, the sequence pair of states of the red line (α𝛼\alphaitalic_α) and blue line (β𝛽\betaitalic_β) determines the transmitted digital signal**C**: When introducing the c... | BAC | ACB | BCA | ABC | Selection 1 |
**A**: There has been extensive study about a family of polynomial maps defined through a parameter a∈𝔽𝑎𝔽a\in\mathbb{F}italic_a ∈ blackboard_F over finite fields**B**: Some well-studied families of polynomials include the Dickson polynomials and reverse Dickson polynomials, to name a few**C**: Conditions for such fa... | ABC | BCA | BAC | BAC | Selection 1 |
**A**:
In this study we only considered different meta-learners within the MVS framework**B**: Some of those classifiers may be expected to perform better in terms of classification performance than the classifiers presented here, but not many have the embedded view selection properties of MVS-based methods. For examp... | BCA | CAB | ACB | ABC | Selection 3 |
**A**: FBED-CART-PS exhibits low sensitivity to noisy variables in terms of both ROC AUC and AP**B**:
Figure 11(b) demonstrates the impact of the number of noisy variables, ranging from 0 to 20, accounting for 0% to 18% of the original variables, with a fixed percentage of anomalies at 10%**C**: This behavior can be a... | CAB | BAC | CAB | CBA | Selection 2 |
**A**: Comparison with Abeille et al**B**: [2021] Abeille et al**C**: [2021] recently proposed the idea of convex relaxation of the confidence set for the more straightforward logistic bandit setting. Our work can be viewed as an extension of their construction to the MNL setting.
| BCA | ABC | CBA | BAC | Selection 2 |
**A**:
Figure 3: Video self-stitching (VSS). a) Snippet-level features are extracted for the entire video**B**: d) Original clip (green dots) and up-scaled clip (orange dots) are stitched into one feature sequence with a gap. **C**: b) Long video is cut into multiple short clips. c) Each video clip is up-scaled along ... | ACB | BAC | CBA | CAB | Selection 1 |
**A**: Indeed, the excessive computational time required for producing new hyperparameters along with ensemble learning methods can be problematic**B**: Despite that, one possible improvement for VisEvol is to utilize parallel processing on powerful cloud servers. Moreover, we believe that the advancements in high-perf... | CBA | ACB | CAB | BCA | Selection 4 |
**A**:
Markov chains and consensus protocols share a close relationship**B**: Notable works such as [23, 24, 25, 26] have leveraged Markov chain theory to provide insights and analysis for consensus protocols.**C**: The rich theory of Markov chains has proven to be valuable in analyzing specific consensus protocols | CAB | ACB | ABC | ABC | Selection 2 |
**A**:
Shape matching can be formulated as bringing points defined on one shape into correspondence with points on another shape**B**: A simple mathematical formulation for doing so is the linear assignment problem (LAP) [49], where a linear cost function is optimised over the set of permutation matrices**C**: The obj... | ABC | ACB | CBA | BAC | Selection 1 |
**A**:
We now introduce a last class of intersection graphs**B**: A rooted path graph is the intersection graph of directed paths in a rooted tree**C**: 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 follow... | CAB | ABC | ACB | CBA | Selection 2 |
**A**: In this paper, we extend the symmetric Laplacian inverse matrix (SLIM) method (SLIM, ) to mixed membership networks and call this proposed method as mixed-SLIM. As mentioned in SLIM , the idea of using the symmetric Laplacian inverse matrix to measure the closeness of nodes comes from the first hitting time in a... | ACB | ACB | ABC | BAC | Selection 3 |
**A**: Our Contribution**B**: Our contribution is two fold**C**: 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 i... | ABC | ACB | BCA | BCA | Selection 1 |
**A**: The reason is that GeneraLight trains several models on diverse generated traffic flows, and select the model in testing by matching the flow**B**: Hence, it limits the generalization once the testing flow differs largely from the training flows.
**C**: Except MaxPressure analysed above, GeneraLight achieves the... | BCA | ACB | BAC | ABC | Selection 1 |
**A**: In terms of analysis techniques, we note that the theoretical analysis of the algorithms we present is specific to the setting at hand and treats items “collectively”**B**: In terms of the experimental analysis, in our experiments, the prediction error is a natural byproduct of the learning phase, and prediction... | BCA | ACB | ABC | BAC | Selection 2 |
**A**: We present Locally Conditioned Atlas (LoCondA), a framework for generating and reconstructing meshes of objects using an atlas of localized charts that leverage the introduced notion of the continuous atlas. It consists of two parts**B**: Secondly, we use a separate neural network that transforms a point from th... | CBA | BCA | CBA | ACB | Selection 4 |
**A**: Wasserstein barycenters, which define the mean of objects that can be modeled as probability measures on a metric space (images, texts, videos), are used in many fields including Bayesian computations [55], texture mixing [50], clustering (k𝑘kitalic_k-means for probability measures) [13], shape interpolation an... | BAC | CBA | CAB | BCA | Selection 2 |
**A**: In [6] the authors characterize them in terms of their corresponding cycle matrices and present a Venn diagram that shows their inclusion relations**B**: Among these classes we can find the strictly fundamental class.**C**:
Different classes of cycle bases can be considered | BCA | CAB | BAC | CAB | Selection 1 |
**A**:
The proof of Theorem 2.1 is quite involved and builds on the method of constrained chain maps developed in [18, 35] to study intersection patterns via homological minors [37]**B**: A major part of this paper, all of Sections 3 and 4, is devoted to adapt it to handle the k𝑘kitalic_k-partite structure of colorfu... | BCA | ACB | ABC | CBA | Selection 2 |
**A**: In Fig. 7(d), we acknowledged a case where, according to the target correlation measure, all logarithmic transformations were sufficient. However, F8_l2 and F8_l10 were better candidates for transformation since the correlation between features decreased (green lines instead of red-colored) when choosing these o... | BCA | 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... | ABC | BCA | BCA | CAB | Selection 1 |
**A**:
It is unknown how well the methods scale up to multiple sources of biases and large number of groups, even when they are explicitly annotated. To study this, we train the explicit methods with multiple explicit variables for Biased MNISTv1 and individual variables that lead to hundreds and thousands of groups f... | ACB | CBA | BCA | CAB | Selection 1 |
**A**: We further suggest several future directions of deep learning-based gaze estimation.
1) Extracting more robust gaze features**B**: The perfect gaze estimation method should be accurate under all different subjects, head poses and environments**C**: Therefore, an environment-invariant gaze feature is crucial. | BAC | BAC | ABC | CBA | Selection 3 |
**A**: Matching approach: Aims to compare the similarity between images using a matching process. Generally, the face image is sampled into a number of patches of the same size**B**: The advantage of this approach is that the sampled patches are not overlapped, which avoids the influence of occluded regions on the othe... | BCA | BCA | ACB | ABC | Selection 3 |
**A**: Moreover, we take the liberty to nest values (boxed and highlighted yellow), which can be expanded into SAX [PP20].**B**:
First, we define head and tail observations on streams of arbitrary depth**C**: Since they are not recursive, we do not bother tracking the size superscript of the typing judgment, since the... | CAB | BAC | BAC | BAC | Selection 1 |
**A**: FairCMS-II has an increase in user-side overhead compared to FairCMS-I, because in FairCMS-II, the user transmits and decrypts the media content while in FairCMS-I, the user transmits and decrypts the D-LUTs. Nevertheless, this user-side efficiency level is substantially the same as the current mainstream media ... | CBA | ABC | ACB | CAB | Selection 1 |
**A**: (2020) is another model that uses an attentional aggregation strategy with residual connections to learn feature representations and model feature interactions. However, even with the use of attention mechanisms to account for the weight of each pair of feature interactions, aggregating all interactions together... | ABC | BCA | CBA | BCA | Selection 3 |
**A**:
Requiring access to a zeroth-order and domain oracle are mild assumptions, that were also implicitly assumed in one of the three FW-variants presented in Dvurechensky et al**B**: [2022] when computing the step size according to the strategy from Pedregosa et al**C**: [2020]; see 5 in Algorithm 4. The remaining ... | BCA | ACB | CAB | ABC | Selection 4 |
**A**: Precisely, the routines are: (1) extend structures along active paths (Extend-Active-Paths), (2) check for edge augmentations (Check-for-Edge-Augmentation), and (3) include (additional) unmatched edges to each structure (Include-Unmatched-Edges). Each of these routines is performed in a separate pass over the ed... | BAC | BAC | BCA | CAB | Selection 3 |
**A**: We provide necessary notation and assumptions in Section II**B**:
The rest of this paper is organized as follows**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. | ABC | CAB | BAC | BCA | Selection 3 |
**A**: Possible interesting areas for further research are related to the practical features that arise in the federated learning setup, such as asynchronous transmissions and information compression to minimize communication costs, among other issues**B**: This is particularly relevant for cases in which the function ... | ABC | ACB | BCA | BAC | Selection 2 |
**A**: It consists of bargaining rounds between a smuggler, who is motivated to import contraband without getting caught, and a sheriff, who is motivated to find contraband or accept bribes**B**: Figure 2(c) shows that JPSRO is capable of finding the optimal value.
**C**: Sheriff (Farina et al., 2019b) is a two-player,... | BCA | BAC | ACB | ACB | Selection 1 |
**A**: However, its optimality is for worst-case adaptive queries, and the guarantees that it offers only beat the naive intervention—of splitting a dataset so that each query gets fresh data—when the input dataset is quite huge (Jung et al., 2020)**B**: A worst-case approach makes sense for privacy, but for statistica... | CAB | BAC | BCA | ACB | Selection 3 |
**A**: We use reduction steps inspired by the kernelization algorithms [12, 46] for Feedback Vertex Set to bound the size of 𝖺𝗇𝗍𝗅𝖾𝗋𝖺𝗇𝗍𝗅𝖾𝗋\mathsf{antler}sansserif_antler in the size of 𝗁𝖾𝖺𝖽𝗁𝖾𝖺𝖽\mathsf{head}sansserif_head, by analyzing an intermediate structure called feedback vertex cut**B**:
Our al... | CBA | ABC | CAB | BAC | Selection 4 |
**A**: They also extended the triplet loss in [19] to contrastive loss.**B**:
In [90], they reframed image harmonization as a background-to-foreground style transfer problem and introduced region-aware adaptive instance normalization (AdaIn) to transfer visual style from the background to the foreground**C**: A succee... | ACB | ABC | CAB | CBA | Selection 3 |
**A**: In addition to the collection and processing of data, it is essential to identify and quantify the correlations between sub-datasets in CityNet to gain insights into the effective utilization of the multi-modal data**B**: By doing so, we aim to provide a deeper understanding of the interconnections between diffe... | ACB | BAC | ABC | CAB | Selection 1 |
**A**: Quantile regression forests generalize this idea by using the property that the conditional distribution can be expressed as a conditional mean:**B**:
Meinshausen meinshausen2006quantile modified the random forest prediction method from the previous section to be able to directly estimate quantiles**C**: Ordin... | CAB | ABC | CBA | ABC | Selection 1 |
**A**: Instead of feeding the token embedding of each of them individually to the Transformer, we can combine the token embedding of either the four tokens for MIDI scores or six tokens for MIDI performances in a group by concatenation and let the Transformer model
process them jointly, as depicted in Fig**B**: We can ... | ACB | ABC | CBA | CAB | Selection 1 |
**A**: to L(k,1)𝐿𝑘1L(k,1)italic_L ( italic_k , 1 )-labeling problem (see e.g**B**: [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.
**C**: This description draws a comparison e.g | CBA | ACB | BCA | CAB | Selection 3 |
**A**: However, in this paper, we consider an intelligent task at the receiver to recover the text information of the input speech signals**B**: Regarding the semantic commutations for speech information, our previous work developed an attention mechanism-based semantic communication system to restore the source messag... | BAC | BCA | ACB | CBA | Selection 1 |
**A**: There are three categories for 3D semantic segmentation methods: projection-based methods, voxel-based methods and point-based methods. Multi-view projection-based methods[20, 21, 22] project the 3D data into 2D from multiple viewpoints, therefore they can easily process the projected data on 2D convolution netw... | BAC | CBA | CAB | ABC | Selection 4 |
**A**: In contrast to these methods, we only use the monocular image as input without any extra burden.**B**: Existing works [6, 28, 26, 25, 5, 10] have considered using external pretrained networks, extra training data, and prior knowledge to improve the performance of monocular 3D object detection.
Particularly, Deep... | CAB | BCA | CBA | BAC | Selection 3 |
**A**: For testing, the short side of images was kept at 640640640640 pixels for CTW1500 and Total-Text, and 1,280 pixels for ICDAR2015, MSRA-TD500 and MLT2017, while retaining their aspect ratios.**B**: The momentum of SGD was set to 0.90.90.90.9**C**: We first used SynthText to pre-train our model for 10 epochs using... | BAC | BCA | CBA | BCA | Selection 3 |
**A**: Specifically, the two proposed methods present two different relationship mapping mechanisms between memory blocks and IP addresses to strike a balance between computational cost and memory use. They can be employed to search for frequently occurring IP addresses in practical applications. The extensive experime... | BAC | ABC | CAB | ACB | Selection 3 |
**A**: It is shown that by properly selecting the sign in front of each Schur complement, some preconditioners are positively stable. Numerical experiments based on the Biot model are provided to show that positively stable preconditioners outperform other preconditioners. More clearly, when inexact elliptic approximat... | CAB | BAC | BCA | BAC | Selection 1 |
**A**: For CIFAR-10 we search for a learning rate in the range [0.0001, 0.00001], for MIMIC-III we search in the range [0.1, 0.001], and for ModelNet40 we search in the range [0.001, 0.00005]**B**:
In each experiment, for each value of Q𝑄Qitalic_Q, we choose the learning rate using a grid search**C**: For each Q𝑄Qit... | CAB | BAC | ABC | ABC | Selection 2 |
**A**: Extensive studies from diverse viewpoints can be found in the references braman2010thirdorder ; Kilmer2013SIAM ; Jin2020 ; Miao2020T ; zheng2020t . Before proceeding with our main results, it is essential to revisit the fundamental concept of T-eigenvalues and T-eigenvectors**B**: Subsequently, we further elabor... | ABC | BAC | BCA | BAC | Selection 3 |
**A**: As shown in Figure 7 (c), the two-stream architecture exhibits superior performance with more visually reasonable structures and detailed textures. Quantitative results in Table 2 also validate the advantages of texture and structure dual generation.
**B**: We enlarge its channels to make it have the same amount... | CBA | ACB | BCA | BCA | Selection 1 |
**A**: The concept of BEC was first introduced by Elias in 1955 InfThe **B**: In a binary erasure channel (BEC), a binary symbol is either received correctly or totally erased with probability ε𝜀\varepsilonitalic_ε**C**: Together with the binary symmetric channel (BSC), they are frequently used in coding theory and in... | CAB | CBA | BAC | BCA | Selection 3 |
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