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**A**: In practice it is the generating set produced by the constructive recognition algorithms from [10, 11] as implemented in MAGMA**B**: Consequently, algorithms in the composition tree data structure, both in MAGMA and in GAP, store elements in classical groups as words in the LGO generators. Moreover, the LGO gene... | BCA | CAB | CAB | ACB | Selection 1 |
**A**: Except for (ii), all steps above above can be performed efficiently as the matrices involved are sparse and either local or independent of hℎhitalic_h**B**: From now on, we concentrate on approximating P𝑃Pitalic_P so that (25) can be accurately and efficiently solved.
**C**: Solving (25) on the other hand invol... | ACB | ABC | CAB | CAB | Selection 1 |
**A**: These coordinates are computed somehow and their true values can differ from their values stored in the computer**B**: 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,... | BAC | BCA | BAC | ABC | Selection 2 |
**A**: Single Tweet Classification Results. The experimental results of are shown in Table 2**B**: The best performance is achieved by the CNN+LSTM model with a good accuracy of 81.19%. The non-neural network model with the highest accuracy is RF**C**: However, it reaches only 64.87% accuracy and the other two non-neur... | CBA | ACB | BAC | ABC | Selection 4 |
**A**: Instead, we should look at the 00–1111 error on the validation dataset**B**: 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.
**C**: We should not rely on plateauing of the training loss or on the loss (lo... | BAC | BCA | CAB | CAB | Selection 2 |
**A**: The results show that the low-level hidden representation of tweets feature is at least the second best features over time**B**: We also derive explanations on the low performance of supposed-to-be-strong high-level features at early stage. The study also indicates that, there is still considerable room to impro... | ACB | CBA | ABC | BCA | Selection 4 |
**A**:
Results**B**: The baseline and the best results of our 1stsuperscript1𝑠𝑡1^{st}1 start_POSTSUPERSCRIPT italic_s italic_t end_POSTSUPERSCRIPT stage event-type classification is shown in Table 3-top**C**: The accuracy for basic majority vote is high for imbalanced classes, yet it is lower at weighted F1. Our le... | BAC | BAC | ABC | ACB | Selection 3 |
**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**: Body weight, according to BMI, is normal for half of the patien... | ACB | BAC | BAC | CBA | Selection 4 |
**A**: Furthermore, it is expected that complex representations at multiple spatial scales are necessary for accurate predictions of human fixation patterns. We therefore incorporated a contextual module that samples multi-scale information and augments it with global scene features**B**: This makes our model suitable ... | ACB | CBA | ABC | CAB | Selection 1 |
**A**: We answer this question in the negative.**B**:
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**C**: This definition leads to the general combinatorial question of whether e... | CBA | ACB | CAB | CBA | Selection 3 |
**A**: Indeed, in a recent survey (Section 7.2 in Machado et al. (2018)) this was formulated as the following challenge: “So far, there has been no clear demonstration of successful planning with a learned model in the ALE”.**B**:
Although prior works have proposed training predictive models for next-frame, future-fra... | ABC | CAB | CBA | BCA | Selection 2 |
**A**: 2**B**: This section describes the primary locomotion modes, rolling and walking locomotion of our hybrid track-legged robot named Cricket shown in Fig**C**: It also introduces two proposed gaits designed specifically for step negotiation in quadrupedal wheel/track-legged robots.
| ABC | CBA | CBA | BAC | Selection 4 |
**A**: It should be fairly clear that such assumptions are very unrealistic or undesirable. Advice bits, as all information, are prone to transmission errors**B**: 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 ahe... | BCA | ACB | CBA | CBA | Selection 2 |
**A**: and highly parallelized nature of SS3 while the “rich and interactive visual information” one by its white-box nature.
**B**: The “large-scale passive monitoring” aspect would be supported by the incremental313131Only one small vector, the confidence vector, needs to be stored for each user**C**: In that context... | ABC | CAB | ACB | CBA | Selection 4 |
**A**: Recently, parameter server (Li et al., 2014) has been one of the most popular distributed frameworks in machine learning**B**: The theories in this paper can also be adapted for the all-reduce framework.**C**: GMC can also be implemented on the parameter server framework.
In this paper, we adopt the parameter se... | CAB | ACB | CBA | BAC | Selection 2 |
**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 | BAC | ABC | Selection 1 |
**A**: However, in this algorithm, only one UAV is allowed to change strategy in one iteration based on current game state, and then another UAV changes strategy in the next iteration based on the new game state. It means that UAVs are not permitted to update strategies at the same time**B**:
The learning rate of the ... | BAC | CAB | ACB | CAB | Selection 1 |
**A**: Note**B**: is shown in figure 20**C**: For this shot
(and simulation), Vcomp=12subscript𝑉𝑐𝑜𝑚𝑝12V_{comp}=12italic_V start_POSTSUBSCRIPT italic_c italic_o italic_m italic_p end_POSTSUBSCRIPT = 12kV and tcomp=45μsubscript𝑡𝑐𝑜𝑚𝑝45μt_{comp}=45\upmuitalic_t start_POSTSUBSCRIPT italic_c italic_o italic_... | CAB | BCA | ACB | BAC | Selection 1 |
**A**: Many of the proposed extensions focus on minimizing the variance that comes from AGE by finding methods to optimize the learning trajectory or from TAE by using methods like averaging to exact DQN parameters. Dropout methods have the ability to assemble these two solutions which minimize different source of vari... | BCA | BAC | ABC | CAB | Selection 4 |
**A**: For a comprehensive review of the natural image datasets that segmentation models are usually benchmarked upon, we direct the interested readers to Lateef and Ruichek (2019).
**B**: Next, we briefly discuss the most popular and widely used datasets for the semantic segmentation of natural images**C**: These data... | ACB | CAB | BCA | BCA | Selection 2 |
**A**: In this way, we learn an efficient representation of the decision boundaries and are able to transform random forests into neural networks implicitly.**B**: To avoid overfitting, the data is generated on-the-fly so that each training example is unique**C**: For training, we generate input-target pairs (x,y)𝑥𝑦(... | CBA | ACB | ACB | ACB | Selection 1 |
**A**: In a more practical setting, the agent sequentially explores the state space, and meanwhile, exploits the information at hand by taking the actions that lead to higher expected total rewards**B**: Such an exploration-exploitation tradeoff is better captured by the aforementioned statistical question regarding th... | BAC | ACB | CBA | ABC | Selection 4 |
**A**: While domain-specific accelerators, such as Google’s TPU, excel in their specific performance, they are usually limited to a set of specific operations and are neither flexible in terms of data types nor sparse calculations**B**: They are not suited to execute generic compressed models and are therefore not incl... | CBA | ACB | CBA | BAC | Selection 2 |
**A**: We thank Prof. Henry Adams and Dr. Johnathan Bush for very useful feedback about a previous version of this article**B**: We thank Dr. Qingsong Wang for bringing to our attention the paper [76] which was critical for the proof of Theorem 1. Finally, we thank Dr. Alexey Balitsky for pointing out an imprecision in... | CAB | BAC | CAB | ACB | Selection 4 |
**A**: Adaptive PCP vs**B**: PCP
Although it is not uncommon to find tools that use PCP views together with DR-based scatterplots (e.g., iPCA [69]) with various schemes for re-ordering and prioritizing the axes (e.g., [70, 71]), the arrangement and presentation of these PCP’s are usually static in order to reflect at... | CAB | CBA | CAB | ABC | Selection 4 |
**A**: As mentioned before, the most popular algorithm in this category is GA [98]. However, many other bio-inspired algorithms exhibit a similar behavior when creating solutions, yet they are inspired by other phenomena, such as Cultural Optimization (CA, [479]) (in the Social Human Behavior category), LA [267] (in th... | CBA | ABC | BCA | BAC | Selection 1 |
**A**: An epoch means a complete training of GAE and an update of the graph**B**: To illustrate the process of AdaGAE, Figure 2 shows the learned embedding on USPS at the i𝑖iitalic_i-th epoch**C**: The maximum number of epochs, T𝑇Titalic_T, is set as 10. In other words, the graph is updated 10 times. Clearly, the emb... | CAB | BAC | BCA | BCA | Selection 2 |
**A**: Like the other studies, (Durumeric et al., 2013, 2014), we provide an option to opt out of our scans. To opt out the network has to provide either its network block (in CIDR notation), domain or ASN through the contact page at https://smap.cad.sit.fraunhofer.de**B**:
∙∙\bullet∙ Consent of the scanned. It is oft... | ABC | BCA | BAC | CAB | Selection 3 |
**A**:
While context did introduce more parameters to the model (7,57575757{,}5757 , 575 parameters without context versus 14,3151431514{,}31514 , 315 including context), the model is still very small compared to most neural network models, and is trainable in a few hours on a CPU**B**: This reinforces the idea that t... | BCA | ACB | BAC | CAB | Selection 2 |
**A**: In fact, the construction to generate these semigroups is quite simple [4, Proposition 4.1] (compare also to 3). The same construction can also be used to generate free monoids as automaton semigroups or monoids. Here, the main difference is that the free monoid in one generator can indeed be generated by an aut... | CBA | BAC | BCA | CAB | Selection 4 |
**A**: Since Wu and Mooney (2019) reported that human-based textual explanations Huk Park et al. (2018) gave better results than human-based attention maps for SCR, we train all of the SCR variants on the subset containing textual explanation-based cues**B**: SCR is trained in two phases. For the first phase, which str... | CBA | ACB | ABC | BAC | Selection 3 |
**A**: We reason that this similarity could be due to the use of privacy policy templates or generators. We also found abundant examples of near-duplicate privacy policies on the same website. We reason that this similarity could be due to the presence of archived versions of privacy policies on the website. Since we a... | ACB | ABC | CBA | ACB | Selection 3 |
**A**: The data set is very imbalanced, with most cases being on the absence side. Skeppstedt et al. [51] used an SVM algorithm to train and build their baseline classifier for this task, and we are going to compare it to our stacking ensemble method in this use case.
**B**: The 300 feature vectors are based on the cou... | ABC | CBA | BCA | ABC | Selection 2 |
**A**: In this paper, we take an empirical approach to systematically investigating these impacting factors and finding when MAML works the best**B**: We conduct extensive experiments over 4 datasets**C**: We first study the effects of data quantity and distribution on the training strategy:
RQ1. Since the parameter in... | BAC | ABC | CBA | CAB | Selection 2 |
**A**:
Figure 3: The considered CC-enabled UAV mmWave network consists of a r-UAV and multiple t-UAVs**B**: UAV position-attitude prediction is performed to obtain the future motion state information (MSI) before next information feedback**C**: The CCA and the beam are shown in detail in the CCA view. | ABC | CAB | ACB | CBA | Selection 1 |
**A**: 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**B**: This will be bootstrapped... | ABC | BCA | BAC | BCA | Selection 3 |
**A**: Going beyond the NTK regime, we prove that, when the value function approximator is an overparameterized two-layer neural network, TD and Q-learning globally minimize the mean-squared projected Bellman error (MSPBE) at a sublinear rate**B**:
Contribution**C**: Moreover, in contrast to the NTK regime, the induce... | CAB | BAC | BCA | ACB | Selection 2 |
**A**:
Table 3 shows that a 2-layer feed-forward neural network (Equation 6) in the depth-wise LSTM outperforms the original computation of the LSTM hidden state which uses only one layer (Equation 5), which is consistent with intuition**B**: The 1-layer LSTM FFN model also archieves a comparable decoding speed compar... | ABC | ACB | CAB | CBA | Selection 2 |
**A**: However, notice that the T0subscript𝑇0T_{0}italic_T start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT quotient of
Struct(σ)Structσ\operatorname{Struct}(\upsigma)roman_Struct ( roman_σ ) is sober when τ=τ⊆iτsubscriptτsubscript𝑖\uptau=\uptau_{\subseteq_{i}}roman_τ = roman_τ start_POSTSUBSCRIPT ⊆ start_POSTSUBSCRIPT itali... | ACB | BCA | ABC | CAB | Selection 2 |
**A**: To demonstrate the effectiveness of each module in our framework, we conduct an ablation study to show the different performances. Additionally, the experimental results of our approach compared with the state-of-the-art methods are exhibited, in both quantitative measurement and visual qualitative appearance. F... | BCA | BCA | CBA | BCA | Selection 3 |
**A**: Then, we propose a novel method, called
stochastic normalized gradient descent with momentum (SNGM), for large-batch training**B**: In this paper, we first review the convergence property of MSGD, one of the most widely used variants of SGD, and analyze the failure of MSGD in large-batch training from an optimiz... | BAC | CAB | ABC | ACB | Selection 1 |
**A**: On a high level, the obstacle is that radius-minimization requires estimating the cost of each approximate solution; counter-intuitively, this may be harder than optimizing the cost (which is what is done in previous results)**B**: See Appendix A for an in-depth discussion.**C**:
Unfortunately, standard SAA app... | ABC | ACB | BAC | BCA | Selection 4 |
**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 | BAC | CBA | ABC | Selection 1 |
**A**: First, MuCo satisfies δ𝛿\deltaitalic_δ-probability to hinder the adversary from matching the combination of QI values. Second, the records cover for each other at the minimum cost, i.e., maintaining the original QI values as much as possible. The procedure is given in Algorithm 1.**B**: We aim to achieve two go... | CBA | BAC | ABC | ABC | Selection 1 |
**A**: X101-64x4d Xie et al. (2017) is then used as large backbone and it boosts 6 mAP against ResNet50. DCN and More Points Train. We adopt more interpolated points during training, by increasing the number of sampled points from original 14 to 26 for coarse prediction head, and from 14 to 24 for fine-grained point he... | BAC | BCA | ACB | CBA | Selection 2 |
**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**: Maybe the presentation below is what was known. **C**:
Here we give an embarrassingly simple presentation of an example of such a function (although it can be shown to be... | CAB | CAB | CBA | BCA | Selection 4 |
**A**: The main advantage of our algorithm compared to OPT-WLSVI and MASTER is its computational efficiency, as demonstrated by Figure 1. The reason is that our algorithm only requires the most recent data to estimate the Q𝑄Qitalic_Q-function, while the other two require the entire history. MASTER additionally require... | BAC | BCA | CAB | ACB | Selection 3 |
**A**: The usage of fake news ranges from self-serving purposes like clickbait for moneymaking (Geçkil et al., 2018) to agendas on a national scale like political manipulation (Allcott and Gentzkow, 2017) and terrorism (Fang, 2021). With the rapid and extensive adoption of social platforms, fake news has come to be mor... | CAB | ABC | ACB | CBA | Selection 1 |
**A**: If 𝐞W3Csubscript𝐞W3C\mathbf{e}_{\text{W3C}}bold_e start_POSTSUBSCRIPT W3C end_POSTSUBSCRIPT is unobservable during the training phase, it becomes less useful and potentially detrimental when computing attention scores during the testing phase**B**: As shown in Figure 2a, we can initially employ an independent ... | CAB | ACB | BCA | CAB | Selection 2 |
**A**: We evaluate the proposed method on several challenging image-based tasks, including 1) Atari games, 2) Atari games with sticky actions, which adds more stochasticity in the environment, 3) Super Mario, which we utilize to evaluate the adaptability of VDM to the novel environments, 4) a Multi-player game, which h... | CBA | BAC | BCA | CAB | Selection 3 |
**A**: The polynomial convergence rates of Floater-Hormann and all**B**: The observations made in 2D remain valid**C**: 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 co... | BAC | BCA | CAB | ACB | Selection 3 |
**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... | CAB | ACB | BCA | BAC | Selection 1 |
**A**: Optical logic aggregates can be designed in the same way as in Implementation of Structural Computer Using Mirrors and Translucent Mirrors, and for the convenience of expression and the exploration of mathematical properties (especially their association with matrices), the number shown in Fig. 5 can be applied ... | ABC | BCA | BCA | BCA | Selection 1 |
**A**: In this paper, we propose a representation of such a group using the concept of linear representation defined through the Koopman operator.**B**:
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**C**: Given a finite ... | CBA | ACB | CAB | ABC | Selection 3 |
**A**: Additionally we considered two real data examples, one considerably harder than the other. Across all our experiments, the relative performance of the nonnegative lasso, nonnegative adaptive lasso and nonnegative elastic net remained remarkably stable. Our results show that MVS can be used with one of these meta... | CBA | CAB | BAC | BCA | Selection 2 |
**A**: This method employs directed acyclic graphs (DAGs) to exploit data sparsity and independence among variables. For each variable, DAGnosis constructs a conformal prediction model, specifically a Conformalized Quantile Regression, to establish prediction intervals at a predefined significance level**B**: If a feat... | BCA | 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**: Then it pools the aggregated features into a smaller temporal scale. Its architecture is illustrated in Fig. 4**B**: The temporal branch contains a Conv1d(3,1)Conv1d31\textrm{Conv1d}(3,1)Conv1d ( 3 , 1 )222For conciseness, we use Conv1d(m,n)Conv1d𝑚𝑛\textrm{Conv1d}(m,n)Conv1d ( italic_m , italic_n ) to repres... | BCA | ABC | BAC | ACB | Selection 1 |
**A**:
At this phase, we want to confirm precisely the cluster affiliation and the relationship with the overall performance (here, the average of 4 validation metrics) for all the models**B**: Performance).**C**: To achieve that, the beeswarm plots in Figure 2(b.1 and b.2) arrange the models according to the distinct... | BCA | BAC | ACB | CAB | Selection 3 |
**A**: The decentralized state-dependent Markov matrix synthesis (DSMC) algorithm is introduced in Section III.
Section IV introduces the probabilistic swarm guidance problem formulation, and presents numerical simulations of swarms converging to desired distributions. The paper is concluded in Section V.**B**: Section... | ACB | BAC | CBA | BCA | Selection 3 |
**A**: However, a major disadvantage is that such an approach has a strong bias due to the choice of the reference.**B**: To do so, one can select one of the shapes as reference, and then solve a sequence of pairwise shape matching problems between each of the remaining shapes and the reference**C**:
In principle, any... | ACB | BAC | BCA | CBA | Selection 4 |
**A**: We want to explain them in details and compute the computational complexity of the algorithm**B**: In this section we analyze all steps of algorithm RecognizePG**C**: Some of these steps are already discussed in [22], anyway, we describe them in order to have a complete treatment.
| CBA | BAC | ABC | CBA | Selection 2 |
**A**:
Dolphins: this network consists of frequent associations between 62 dolphins in a community living off Doubtful Sound**B**: In the Dolphins network, node denotes a dolphin, and edge stands for companionship dolphins0 ; dolphins1 ; dolphins2 **C**: The network splits naturally into two large groups females and m... | ABC | ACB | CAB | CBA | Selection 1 |
**A**: (2016); Chen et al. (2016); Dalalyan (2017); Chen et al. (2017); Raginsky et al. (2017); Brosse et al. (2018); Xu et al**B**: (2018); Cheng and Bartlett (2018); Chatterji et al. (2018); Wibisono (2018); Bernton (2018); Dalalyan and Karagulyan (2019); Baker et al. (2019); Ma et al. (2019a, b); Mou et al. (2019); ... | ACB | BCA | ABC | BAC | Selection 2 |
**A**: To solve this problem, several optimization-based methods have been proposed to optimize average travel time, throughput, etc., which decide the traffic signal plans according to the dynamical observed data.
Specifically, the method [2] calculates the difference between the number of upstream and downstream vehi... | BAC | ACB | CBA | BCA | Selection 3 |
**A**: Here, the algorithm’s performance is evaluated only at the extreme cases in which the advice is either error-free or adversarially generated, namely with respect to its consistency and its robustness, respectively**B**:
Online bin packing was recently studied under an extension of the advice complexity model, i... | BAC | ABC | CBA | BCA | Selection 1 |
**A**: Therefore LoCondA uses only the base’s data model during training, which increases the efficiency and applicability of our approach.**B**: To that end, we propose a novel framework, LoCondA, capable of generating and reconstructing high-quality 3D meshes**C**: This framework extends the existing base hypermodels... | BAC | CAB | CBA | ACB | Selection 2 |
**A**: The Mirror-prox algorithm can be performed in a decentralized manner, however, it is not known whether its optimality is preserved.
In this paper, we prove that Mirror-prox remains optimal even in a decentralized case w.r.t**B**: the dependence on the desired accuracy ε𝜀\varepsilonitalic_ε and condition number ... | ABC | CBA | ACB | ACB | Selection 1 |
**A**:
Different classes of cycle bases can be considered**B**: Among these classes we can find the strictly fundamental class.**C**: In [6] the authors characterize them in terms of their corresponding cycle matrices and present a Venn diagram that shows their inclusion relations | BCA | CAB | ACB | ABC | Selection 3 |
**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... | ABC | CAB | ACB | ABC | Selection 2 |
**A**: He has approximately 3.5 years of experience with ML, and he currently works with reinforcement learning.
The second ML expert (E2) is a senior researcher in software engineering and applied ML working in a governmental research institute as an adjunct professor**B**: The third expert (E3) is an associate profes... | CBA | BAC | BAC | ACB | Selection 4 |
**A**: For the initialization phase needed to train the GPs in the Bayesian optimization, we select 20 samples over the whole range of MPC parameters, using Latin hypercube design of experiments**B**: After the initial learning phase the algorithm quickly finds the region where the simulation is feasible with respect t... | BCA | ACB | CAB | BAC | Selection 2 |
**A**: While this is a toy problem, in the real world, hidden minority patterns are common and failing on them can have dire consequences**B**: Systems designed to aid human resources, help with medical diagnosis, determine probation, or loan qualification could be biased against minority groups based on age, gender, r... | ABC | BCA | BCA | BCA | Selection 1 |
**A**: We mark the top three performance in all benchmarks with underlines.**B**: The 3D gaze estimation also are divided into within-dataset and cross-dataset evaluation**C**: We also convert the two definitions with post-processing methods following Sec. 4.2.2.
We respectively conduct benchmarks for 2D PoG and 3D gaz... | BAC | ACB | CBA | BAC | Selection 3 |
**A**: Next, the whole features are quantized to compute a codebook. Test image features are then assigned to the nearest code in the codebook to be represented by a histogram.
In the literature, the BoF paradigm has been largely used for handcrafted feature quantization lobel2013joint to accomplish image classificati... | CAB | CBA | ACB | BAC | Selection 4 |
**A**: Relatedly, refer to Das and Pfenning [DP20a] for a proof of type safety for a session type system with arithmetic refinements**B**: In contrast to the termination proof for base SAX [DPP20], we explicitly construct a model of SAX in sets of terminating configurations, also known as semantic typing [App01, HLKB21... | BCA | ABC | CBA | ABC | Selection 1 |
**A**: Notably, both FairCMS-I and FairCMS-II fulfill scalability and owner-side efficiency requirements. In summary, the two proposed schemes can facilitate the media sharing of owners, while simultaneously ensuring the joint protection of copyright and users’ rights, ultimately promoting the sustainable growth of the... | ACB | CBA | BAC | CAB | Selection 2 |
**A**: (2018).
Each layer of our proposed model produces higher-order interactions based on the existing ones and thus the highest-order of interactions is determined by layer depth.**B**: Specifically, to accommodate the polysemy of feature interactions in different semantic spaces, we utilize a multi-head attention m... | CAB | ACB | ACB | ABC | Selection 1 |
**A**: We can make use of the proof of convergence in primal gap to prove linear convergence in Frank-Wolfe gap**B**: In order to do so, we recall a quantity formally defined in Kerdreux et al**C**: [2019] but already implicitly used earlier in Lacoste-Julien & Jaggi [2015] as:
| ACB | BCA | ACB | ABC | Selection 4 |
**A**: By design of our algorithm, if an arc a𝑎aitalic_a is active at the beginning of p𝑝pitalic_p, it remains active until the end of the execution of Extend-Active-Paths**B**: Consider a Pass-Bundle p𝑝pitalic_p and the execution of Extend-Active-Paths**C**: Only possibly at the end of Extend-Active-Paths the algor... | BAC | ACB | CAB | CBA | Selection 1 |
**A**: Techniques to remedy this increased communication costs include gradient difference compression [34, 51, 52] and error compensation [37, 53, 54], which enjoy better performance than direct compression.
In [55], the difference compression (DCD-PSGD) and extrapolation compression (ECD-PSGD) algorithms were propose... | CAB | BAC | ACB | CBA | Selection 4 |
**A**: For this case we present Algorithm 2. This algorithm is the Tseng method [44] with a resolvent/proximal operator calculation (4)**B**: The problem (4) is divided into two minimization subproblems, by X𝑋Xitalic_X, and by Y𝑌Yitalic_Y. Hence, the problem (4) is solved by Fast Gradient Descent. Further, we note th... | BCA | ACB | CBA | CBA | Selection 2 |
**A**: Computing the argmaxargmax\operatorname*{argmax}roman_argmax of the BRs can be achieved through RL or exactly traversing the game tree.
**B**: In practice, we only calculate a BR for positive support policies (similar to Rectified Nash (Balduzzi et al., 2019)**C**: Therefore the CE BR attempts to exploit each po... | CBA | ACB | BAC | BAC | Selection 1 |
**A**: (2011)) proposes relaxed privacy definitions that leverage the natural noise introduced by dataset sampling to achieve more average-case notions of privacy. This builds on intuition that average-case privacy can be viewed from a Bayesian perspective, by restricting some distance measure between some prior distri... | ACB | CAB | CAB | BCA | Selection 4 |
**A**: The remainder of the paper is organized as follows. After presenting preliminaries on graphs and sets in Section 2, we prove the mentioned hardness results in Section 3**B**: We present structural properties of antlers and how they combine in Section 4. In Section 5 we show how color coding can be used to find a... | ABC | ACB | BCA | BCA | Selection 1 |
**A**: [145] proposed to predict the location and scale of inserted object by taking the background image and object layout as input**B**: Generative approaches:
Tan et al**C**: Besides, the bounding box prediction task is converted to a classification task by discretizing the locations and scales. | BAC | ABC | ABC | ACB | Selection 1 |
**A**: Problem Statement**B**: To address the taxi dispatching task, we learn a real-time dispatching policy based on historical passenger requests**C**: At every timestamp τ𝜏\tauitalic_τ, we use this policy to dispatch available taxis to current passengers, with the aim of maximizing the total revenue of all taxis in... | BCA | ABC | ACB | BAC | Selection 2 |
**A**: Moreover, some general conclusions that can be used in future applications or research are derived.
**B**: In this and the following section some of the models introduced above are experimentally investigated**C**: They are evaluated and compared based on some general performance measures | ABC | CBA | ACB | CAB | Selection 4 |
**A**: We only add tempo token at the beginning of the song and the timing when tempo changes. For MIDI scores, the Velocity and Tempo tokens are simply dropped.**B**: It is placed behind the Sub-bar token to imply when the song would perform with the tempo**C**: For MIDI performances, a musical note is represented by ... | ABC | CAB | BCA | CBA | Selection 4 |
**A**: Next, let us count the total number of jumps necessary for finding central vertices over all loops in Algorithm 1**B**: Thus, if in the next iteration we start at exactly the neighbor of the previous central vertex, there can be only O(n)𝑂𝑛O(n)italic_O ( italic_n ) such jumps in total.
**C**: As it was stated... | CAB | CAB | ACB | BAC | Selection 3 |
**A**:
The rest of this article is structured as follows**B**: In Section III, the details of the proposed DeepSC-SR is presented. Simulation results are discussed in Section IV and Section V draws conclusions.**C**: Section II introduces the model of semantic communication system for speech recognition and performanc... | BAC | BCA | ACB | CBA | Selection 3 |
**A**: Thus, this method still requires a large amount of manual labeling. [11] proposes to generate pseudo point-level label using 3D class activation map[12] from subcloud-level annotation, which is similar to the 2D WSSS methods using image-level labels. [13] directly trains a point cloud segmentation network with 1... | CAB | BCA | BCA | BAC | Selection 4 |
**A**:
Figure 6: Qualitative results of our method for Bird’s-Eye-View**B**: We use black box for ground-truth, red box for baseline results, and blue box for our results**C**: All the illustrated images are from the KITTI val set. Zoom in on the circles for more detailed comparison. | CBA | BAC | BAC | ABC | Selection 4 |
**A**: However, their method still suffered from false negatives when both horizontal and vertical text maps had defects.**B**: ContourNet [11] tried to suppress non-text areas by considering text maps in horizontal and vertical directions, which effectively suppressed false positives**C**:
A second prior approach is ... | ACB | ABC | ABC | CBA | Selection 4 |
**A**: The Compute Unified Device Architecture (CUDA) is a parallel computing platform for general computing on GPUs. Most parallel sorting algorithms are variants of standard, well-known sorting algorithms adapted to GPU hardware architecture**B**: For example, Cederman designed a quick sort for the GPU platform Ceder... | BCA | CAB | BAC | ABC | Selection 1 |
**A**: The authors would like to thank Mingjian Ding, and Baoxuan Zhu for providing an alternative proof of the Hurwitz stability of polynomials (25). They also thank Jarle Sogn for communicating on Schur complement based preconditioners.
The work of M. Cai is partially supported by the NIH-RCMI grant through 347 U54MD... | ACB | CAB | ABC | BCA | Selection 3 |
**A**: MIMIC-III:
We train an LSTM model using the MIMIC-III (Medical Information Mart for Intensive Care) dataset, (Johnson et al., 2016), which consists of anonymized information of patients admitted to critical care units in a hospital**B**: Each sample consists of 48484848 time steps corresponding to 48 hours, and ... | CBA | CBA | ACB | CBA | Selection 3 |
**A**: Subsection 4.2 is dedicated to the examination of various properties of pseudospectra related to third-order tensors. Finally, in Subsection 4.3, we present plots illustrating the computed results of ε𝜀\varepsilonitalic_ε-pseudospectra for given tensors and give an example to illustrate the application for seek... | BAC | CAB | BAC | ACB | Selection 2 |
**A**: We quantitatively evaluate the proposed method using three major metrics: LPIPS, PSNR and SSIM, and compare the scores to those of the state-of-the-art counterparts with irregular mask ratios of 0-20%, 20-40% and 40-60%**B**:
Objective evaluation**C**: Table 1 shows the results achieved on the Places2 dataset, ... | CAB | BAC | ACB | CBA | Selection 2 |
**A**: 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 BEC. Here we consider more generally a q𝑞qitalic_q-ary erasure channel ... | BCA | BCA | CBA | CAB | Selection 3 |
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