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**A**: The LGO generating set offers a variety of advantages**B**: In practice it is the generating set produced by the constructive recognition algorithms from [10, 11] as implemented in MAGMA**C**: Consequently, algorithms in the composition tree data structure, both in MAGMA and in GAP, store elements in classical g... | ACB | BCA | ABC | ACB | Selection 3 |
**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... | CAB | ABC | ACB | CAB | 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... | CAB | ACB | ABC | CBA | Selection 4 |
**A**:
We use the same dataset described in Section 5.1. In total –after cutting off 180 events for pre-training single tweet model – our dataset contains 360 events and 180 of them are labeled as rumors**B**: Those rumors and news fall comparatively evenly in 8 different categories, namely Politics, Science, Attacks,... | BAC | ABC | BCA | BCA | Selection 2 |
**A**: The follow-up paper (Gunasekar et al., 2018) studied this same problem with exponential loss instead of squared loss**B**: Under additional assumptions on the asymptotic convergence of update directions and gradient directions, they were able to relate the direction of gradient descent iterates on the factorized... | ACB | ABC | BAC | CAB | Selection 2 |
**A**: There might be some certain delay, as we retrieve only tweets in English and the very first tweets were probably in German**B**: The tweet is ”Sadly, i think there’s something terrible happening in #Munich #Munchen. Another Active Shooter in a mall. #SMH”.**C**:
At 18:22 CEST, the first tweet was posted | CBA | CBA | BCA | ABC | Selection 3 |
**A**: We then evaluate our ensemble ranking model (results from the cascaded evaluation) and show it robustly improves the baselines for all studied cases (RQ3). Notice that, we do not use the learned classifier in Section 5.2 for our ensemble model, since they both use the same time period for training, but opt for t... | ABC | BAC | ACB | CAB | Selection 4 |
**A**: The only difference happens to patient 10 and 12 whose intakes are earlier at day.
Further, patient 12 takse approx**B**: The insulin intakes tend to be more in the evening, when basal insulin is used by most of the patients**C**: 3 times the average insulin dose of others in the morning. | CBA | BAC | CAB | ACB | Selection 2 |
**A**: By contrast, the remaining metrics quantify saliency approximations after convolving gaze locations with a Gaussian kernel and representing the target output as a probability distribution. We refer readers to an overview by Bylinskii et al. (2018) for more information regarding the implementation details and pro... | BCA | ABC | CAB | ABC | Selection 3 |
**A**: Regarding the question of how repetitions of a word affect its locality number, we can show the following result (see the Appendix for a proof).**B**:
A repetitive structure often leads to high locality**C**: For example, note that tutustuttu from above is nearly a repetition | CAB | BCA | CBA | ABC | Selection 1 |
**A**: The work of Henryk Michalewski was supported by the Polish National Science Center grant UMO-2018/29/B/ST6/02959. We gratefully acknowledge Polish high-performance computing infrastructure PLGrid (HPC Centers: ACK Cyfronet AGH, PCSS) for providing computer facilities and support within computational grants no**B... | CBA | BAC | CAB | ACB | Selection 2 |
**A**: In order to account for the robot’s dynamics and precisely quantify energy consumption during step negotiation, we utilized the Vortex physical engine incorporated within CoppeliaSim (previously known as V-REP) robotics simulation software [25]**B**: Our choice of CoppeliaSim as the robot modeling and simulation... | BAC | ACB | ABC | CAB | Selection 2 |
**A**: In addition, the known advice models often allow
information that one may arguably consider unrealistic, e.g., an encoding of some part of the offline optimal solution. Last, and perhaps more significantly, a malicious entity that takes control of the advice oracle can have a catastrophic impact**B**: It should ... | CAB | CBA | CBA | BAC | Selection 4 |
**A**: Only a dictionary of term-frequency pairs is needed for each category.
Then, during training, dictionaries are updated as new documents are processed —i.e**B**: This brief subsection describes the training process, which is trivial**C**: unseen terms are added and frequencies of already seen terms are updated. | CBA | BAC | BCA | ACB | Selection 2 |
**A**: Due to the larger compressed error introduced by RBGS compared with top-s𝑠sitalic_s when selecting the same number of components of the original vector to communicate, vanilla error feedback methods usually fail to converge**B**: Since DEF-A enhances the generalization performance of DEF, we only consider DEF-A... | CAB | ACB | CAB | CAB | Selection 2 |
**A**: operation.**B**: Using cross-correlation would produce the same results and would not require flipping the kernels during visualization**C**:
, where ∗*∗ is the convolution333We use convolution instead of cross-correlation only as a matter of compatibility with previous literature and computational frameworks | BCA | ABC | CBA | ABC | Selection 3 |
**A**: Some algorithms that have been applied in the potential game can also be employed in the UAV ad-hoc network game**B**: Since the UAV ad-hoc network game is a special type of potential game, we can apply the properties of the potential game in the later analysis**C**: In the next section, we investigate the exist... | ACB | BAC | ABC | ACB | Selection 2 |
**A**: and the symbol /\,/\,/ represents Hadamard division, piecewise element-by
element division (e.g.,formulae-sequence𝑒𝑔e.g.,italic_e **B**: , (a¯/b¯)i=ai/bisubscript¯𝑎¯𝑏𝑖subscript𝑎𝑖subscript𝑏𝑖(\overline{a}\,/\,\overline{b})_{i}=a_{i}/b_{i}( over¯ start_ARG italic_a end_ARG / over¯ start_ARG italic_b end_AR... | BCA | ACB | BCA | CBA | Selection 2 |
**A**: This type of variance leads to converging to sub-optimal policies and brutally hurts DQN performance. The second source of variance Target Approximation Error which is the error coming from the inexact minimization of DQN parameters**B**:
The sources of DQN variance are Approximation Gradient Error(AGE)[23] and... | ACB | CAB | BAC | CBA | Selection 3 |
**A**: Ideally, seeing the whole object of interest in a 3D volume might help to capture the geometrical information of the object, which might be missed in processing a 3D volume slice by slice. Therefore a future direction in this area can be through analysis of sequenced models versus volumetric convolution-based ap... | CBA | ACB | CBA | CAB | Selection 4 |
**A**:
Welbl (2014) and Biau et al. (2019) follow a similar strategy**B**: 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 neuron... | ACB | CAB | BCA | CBA | Selection 1 |
**A**: Moreover, we prove that, even when the reward functions are adversarially chosen across the episodes, OPPO attains the same regret in terms of competing with the globally optimal policy in hindsight (Cesa-Bianchi and Lugosi, 2006; Bubeck and Cesa-Bianchi, 2012)**B**: Such a notion of robustness partially justifi... | CAB | BCA | ACB | BAC | Selection 3 |
**A**: (2018b) introduced a ResNet-inspired architecture called ShuffleNet which employs 1×1111\times 11 × 1 grouped convolutions since 1×1111\times 11 × 1 convolutions have been identified as computational bottlenecks in previous works, e.g., see Howard et al. (2017a).**B**: (2017) used grouped convolutions to enlarge... | ACB | ACB | CAB | CBA | Selection 4 |
**A**: Here we study the effect of additive distortion.
**B**: In [64], Liu studies the mapping properties of the filling radius**C**: His results can be interpreted as providing certain guarantees for how the filling radius changes under multiplicative distortion of metrics | CBA | CAB | CBA | BAC | Selection 2 |
**A**: Apart from the adaptive filtering and re-ordering of the axes, we maintained a rather standard visual presentation of the PCP plot, to make sure it is as easy and natural as possible for users to inspect it**B**: The colors reflect the labels of the data with the same colors as in the overview (Subsection 4.2), ... | CBA | ABC | CBA | CBA | Selection 2 |
**A**:
A literature review and critical analysis of metaheuristics recently developed - 2024 [38]: This review focuses on algorithms with titles containing words such as ‘new’, ‘hybrid’, or ‘improved’, in response to the growing trend of nature-based approaches**B**: After analyzing over 100 algorithms, it was found t... | CBA | BCA | CBA | ABC | Selection 4 |
**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**: The main c... | CBA | ACB | CBA | BCA | Selection 4 |
**A**: The results from the tests are stored in the backend database**B**: We next explain each measurement technique. In our measurements in Section 4 we compare the success and applicability of each technique.
**C**: The GUI displays the results of the measurements at https://smap.cad.sit.fraunhofer.de | BCA | ABC | ACB | ABC | Selection 3 |
**A**: Drawing motivation from nature, this paper introduced an approach based on continual adaptation. A recurrent neural network uses a sequence of previously seen gas recordings to form a representation of the current state of the sensors**B**: It then modulates the skill of odor recognition with this context, allow... | CAB | BCA | BAC | ABC | Selection 2 |
**A**: The construction used to prove Theorem 6 can also be used to obtain results which are not immediate corollaries of the theorem (or its corollary for automaton semigroups in 8)**B**: The version for automaton semigroups does not follow directly from 8, as the free monogenic semigroup is not a complete automaton s... | CBA | ABC | ACB | CBA | Selection 3 |
**A**: We next present a quantitative assessment of visual grounding, which does not suffer from the confirmation bias.**B**:
Presentation of qualitative examples in visual grounding models for VQA suffers from confirmation bias i.e., while it is possible to find qualitative samples that look at relevant regions to an... | CAB | BAC | ABC | ABC | Selection 1 |
**A**: We found that the vast majority of documents were in English**B**: The complete set of documents was divided into 97 languages and an unknown language category**C**: We set aside candidate documents that were not identified as English by Langid and were left with 2.1 million candidates.
| BAC | CBA | BCA | ACB | Selection 1 |
**A**: In numerous Kaggle competitions [20], stacking ensembles led to award-winning results**B**: Indeed, one of the major challenges in stacking is to select the best combinations of algorithms and models when designing a stacking ensemble from scratch. This issue may keep machine learning (ML) practitioners and expe... | BCA | ABC | CAB | ACB | Selection 4 |
**A**: We follow the other hyperparameter settings in [Madotto et al., 2019].**B**: In Weibo, we use Gensim [Rehurek and Sojka, 2010]**C**: We use Transformer [Vaswani et al., 2017] as the base model in dialogue generation experiment.
In Persona, we use pre-trained Glove embedding [Pennington et al., 2014] | ACB | BAC | CAB | CBA | Selection 4 |
**A**:
The specialized codebook design of the DRE-covered CCA for multi-UAV mobile mmWave communications**B**: The newly proposed CA codebook can fully exploit the potentials of the DRE-covered CCA to offer full spatial coverage. Moreover, the corresponding codeword selection scheme is also carefully designed to facil... | ACB | CBA | BAC | CBA | Selection 1 |
**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... | BCA | BCA | CBA | ABC | Selection 4 |
**A**: Szepesvári, 2018; Dalal et al., 2018; Srikant and Ying, 2019) settings. See Dann et al. (2014) for a detailed survey. Also, when the value function approximator is linear, Melo et al. (2008); Zou et al**B**: See Geist and Pietquin (2013); Bertsekas (2019) for a detailed survey. When the value function approximat... | CBA | BAC | CBA | ACB | Selection 4 |
**A**: The computation of depth-wise LSTM is the same as the conventional LSTM except that depth-wise LSTM connects stacked Transformer layers instead of tokens in a token sequence as in conventional LSTMs. The gate mechanisms in the original LSTM are to enhance its ability in capturing long-distance relations and to a... | ACB | CBA | CAB | CBA | Selection 1 |
**A**: We define the 𝖥𝖮[σ]𝖥𝖮delimited-[]σ\mathsf{FO}[\upsigma]sansserif_FO [ roman_σ ] formulæ φ≜∃x.∃y.¬(x=y)formulae-sequence≜𝜑𝑥𝑦𝑥𝑦\varphi\triangleq\exists x.\exists y.\neg(x=y)italic_φ ≜ ∃ italic_x **B**:
Consider the logical product space Z𝑍Zitalic_Z of the family (Xi)i∈Isubscriptsubscript𝑋𝑖𝑖𝐼(X_{i})... | CBA | CAB | BAC | BCA | Selection 3 |
**A**: Accurately estimating the distortion parameters derived from a specific camera, is a crucial step in distortion rectification. However, two main limitations that make the distortion parameters learning challenging**B**: (i) The distortion parameters are not observable and hard to learn from a single distorted im... | ACB | BAC | ABC | BAC | Selection 3 |
**A**: We do not adopt any learning rate decay or warm-up strategies.
The model is trained with 10 epochs.**B**: The momentum coefficient is set as 0.9 and the weight decay is set as 0.001**C**: The initial learning rate is selected from {0.001,0.01,0.1}0.0010.010.1\{0.001,0.01,0.1\}{ 0.001 , 0.01 , 0.1 } according to ... | CAB | CBA | BAC | ABC | Selection 1 |
**A**: Nathaniel Grammel and Leonidas Tsepenekas were supported in part by NSF awards CCF-1749864 and CCF-1918749, and by research awards from Amazon and Google**B**: Brian Brubach was supported in part by NSF awards CCF-1422569 and CCF-1749864, and by research awards from Adobe**C**: Aravind Srinivasan was supported i... | CAB | BAC | ACB | CBA | Selection 2 |
**A**: Both the weights of different edges in the network graphs at the same time instant and the network graphs at different time instants may be mutually dependent.) rather than i.i.d**B**: graph sequences as in [12]-[15],
and additive and multiplicative communication noises may co-exist in communication links ([21])... | BAC | CBA | ABC | BCA | Selection 4 |
**A**: While the approaches of k𝑘kitalic_k-anonymity family sanitize the original microdata and publish the anonymized version of microdata. Therefore, differential privacy is inapplicable to the scenario we addressed in this paper.
**B**: Differential privacy adds random noise to the answers of the queries issued by ... | ACB | CAB | CBA | CAB | Selection 3 |
**A**: P6 level of FPN is also added for both coarse prediction head and fine-grained point head, which finally yields 74.3 mAP on our splitted validation set. Other tricks we tried on PointRend give little improvement, including MaskScoring head, GC Block and DoubleHead Wu et al. (2020).
In the following, we refer th... | CAB | ACB | BAC | CBA | Selection 4 |
**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**... | ABC | BAC | BAC | CAB | Selection 4 |
**A**: We derived a minimax regret lower bound for nonstationary linear MDPs to demonstrate that our proposed algorithms are near-optimal. Specifically, when the local variations are known, LSVI-UCB-Restart is near order-optimal except for the dependency on feature dimension d𝑑ditalic_d, planning horizon H𝐻Hitalic_H,... | BAC | CAB | BAC | BCA | 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... | BAC | ACB | CAB | BCA | Selection 3 |
**A**: It also distinguishes DAN from other existing inductive methods that primarily focus on new or unknown entities [19, 20, 21, 22, 23, 24, 25].
**B**: This collective voting mechanism helps mitigate bias and contributes to improved performance, even on traditional tasks**C**: Moreover, DAN introduces a distinctive... | BCA | CBA | BAC | BAC | Selection 2 |
**A**: Normalization methods**B**: We normalize the intrinsic reward and advantage function in training for more stable performance**C**: Since the reward generated by the environment are typically non-stationary, such normalization is useful for a smooth and stable update of the value function. In practice, we normali... | ACB | ABC | ACB | CAB | Selection 2 |
**A**: As expected, (Chebyshev) polynomial interpolation on uniform grids (uniform) and multi-linear interpolation also do not converge.**B**: It is therefore inappropriate for
approximating strongly varying functions, such as the Runge function**C**: Further, we recognize that the Vandermonde approach is inaccurate an... | ABC | BCA | CBA | BCA | Selection 3 |
**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 | CAB | BCA | ABC | Selection 2 |
**A**: Fig. 7 shows, however, that some rays of light can be counted on the lower beta signal, which can interfere with the operation of other Thus, a black body gate was implemented using i cells to make input everywhere into NULL state**B**: Optical logic aggregates can be designed in the same way as in Implementatio... | ACB | ABC | BAC | ACB | Selection 3 |
**A**:
A finite field, by definition, is a finite set, and the set of all permutation polynomials over the finite field forms a group under composition**B**: In this paper, we propose a representation of such a group using the concept of linear representation defined through the Koopman operator.**C**: Given a finite ... | CBA | ACB | BAC | ABC | Selection 2 |
**A**: In the other 5 views, we randomly determine 50% of the features to have a relationship with the outcome. The relationship between features and response is determined by a logistic regression model, where each feature related to the outcome is given a regression weight. In the setting with 30 views, we use the sa... | BAC | ACB | BCA | BCA | Selection 1 |
**A**:
In summary, the DepAD methods FBED-CART-RZPS, FBED-CART-PS, and FBED-CART-Sum generally demonstrate good performance in terms of ROC AUC**B**: It is noteworthy that FBED-CART-PS is the same algorithm proposed in [4].**C**: Among them, FBED-CART-PS and FBED-CART-Sum are considered good choices as they exhibit fa... | ABC | ACB | ABC | CBA | Selection 2 |
**A**: [2020] to a multinomial problem, their setting is materially different from ours**B**:
Comparison with Amani & Thrampoulidis [2021] While the authors in Amani & Thrampoulidis [2021] also extend the algorithms of Faury et al**C**: They model various click-types for the same advertisement (action) via the multino... | BAC | CBA | CBA | BCA | Selection 1 |
**A**: Cross-scale graph network. The xGN module contains a temporal branch to aggregate features in a temporal neighborhood, and a graph branch to aggregate features from intra-scale and cross-scale locations**B**: The temporal branch contains a Conv1d(3,1)Conv1d31\textrm{Conv1d}(3,1)Conv1d ( 3 , 1 )222For concisenes... | BAC | CAB | ABC | ACB | 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... | ABC | BAC | CAB | BCA | Selection 1 |
**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**: The pap... | CAB | ABC | ACB | BCA | Selection 1 |
**A**: 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**B**:
Shape matching can be formulated as bringing points defined on one shape into correspondence with points on another shape**C**: The obj... | BCA | ACB | BAC | ABC | Selection 3 |
**A**: A rooted path graph is the intersection graph of directed paths in a rooted tree**B**: 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:**C**:
We now introduce a last class of intersection gr... | CAB | ABC | BCA | CAB | Selection 3 |
**A**:
The stochastic blockmodel (SBM) (SBM, ) is one of the most used models for community detection in which all nodes in the same community are assumed to have equal expected degrees. Some recent developments of SBM can be found in (abbe2017community, ) and references therein. Since in empirical network data sets, ... | CBA | BAC | ABC | BAC | Selection 3 |
**A**: See, e.g., Udriste (1994); Ferreira and Oliveira (2002); Absil et al. (2009); Ring and Wirth (2012); Bonnabel (2013); Zhang and Sra (2016); Zhang et al. (2016); Liu et al**B**: (2018); Boumal et al. (2018); Bécigneul and Ganea (2018); Zhang and Sra (2018); Sato et al. (2019); Zhou et al. (2019); Weber and Sra (2... | BCA | CAB | CAB | ACB | Selection 4 |
**A**:
3) MetaVIM outperforms Individual RL, MetaLight and PrssLight with 827, 423 and 411, respectively**B**: The main reason is that they learn the traffic signal’s policy only using its own observation and ignore the influence of the neighbors, while MetaVIM considers the neighbors as the unobserved part of the cur... | ACB | ABC | CAB | CAB | Selection 2 |
**A**: An important application of online bin packing is Virtual Machine (VM) placement in large data centers**B**: In the context of this application, the consolidation ratio (?) is the number of VMs per host, in typical scenarios. Note that the consolidation ratio is typically much smaller than k𝑘kitalic_k.**C**: He... | ABC | BAC | BAC | ACB | Selection 4 |
**A**: (2020) added terms to prevent patch collapse, reduce patch overlap and calculate the exact surface properties analytically rather than approximating them. Deng et al**B**: To address the problem mentioned above, most of the methods extend the Chamfer loss function of basic AtlasNet with additional terms. Bednari... | ABC | CBA | ABC | BAC | Selection 4 |
**A**: Paper organization. This paper is organized as follows**B**: In Section 4, we present the lower complexity bounds for saddle point problems without individual variables. Finally in Section 5, we show how the proposed algorithm can be applied to the problem computing Wasserstein barycenters .
**C**: Section 2 pre... | ABC | BAC | CAB | ACB | 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... | ACB | BAC | BAC | CBA | Selection 1 |
**A**: One immediate application of Theorem 1.2 is the reduction of fractional Helly numbers**B**: of Patáková [35, Theorem 2.3] into:
**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 | BCA | CBA | ACB | Selection 4 |
**A**: For precision and recall, we always use macro-average, which is identical to Mansouri et al. [94]**B**: On the one hand, the precision was 4% lower in both test and external validation sets for our analysis. On the other hand, the recall was 5% higher for the test set and 9% higher for the external validation da... | BCA | CBA | ABC | ABC | Selection 1 |
**A**: We first optimize the performance of the simulated positioning system by adding a receding horizon MPCC stage where we pre-optimize the position and velocity references provided to the low level controller**B**: The weights in the MPCC cost terms are manually tuned, the controller gains are kept at their nominal... | BCA | ABC | BAC | ACB | Selection 4 |
**A**: We further study bias exploitation on CelebA**B**: For this, we plot improvement over the standard model (IOSM𝐼𝑂𝑆𝑀IOSMitalic_I italic_O italic_S italic_M) in Fig. 5, which is the accuracy gain over the standard model on each dataset group. The improvements in blond (minority group) incur degradation in no... | BCA | ACB | ACB | CAB | Selection 1 |
**A**:
TABLE V: \addedBenchmark of within-dataset evaluation**B**: The underlines indicate the top three best performances. Note that the methods in the last row are proposed for point of gaze estimation, we convert the result using the post-processing method in Sec. 4.2.**C**: We use the provided source codes or re-i... | BCA | ACB | BAC | ABC | Selection 2 |
**A**: The highest recognition rate is achieved by the ResNet-50 through the quantization of DRF features by 88.9%**B**: This performance is achieved using 70 codewords that feed an MLP classifier. AlexNet model realized good recognition rates comparing to the VGG-16 model (86.0% vs 85.6% as highest rates).**C**:
Tabl... | BAC | BCA | CBA | BAC | Selection 2 |
**A**:
In this section, we extend SAX [DPP20] with recursion and arithmetic refinements in the style of Das and Pfenning [DP20b]**B**: SAX is a logic-based formalism and subsuming paradigm [Lev04] for concurrent functional programming that conceives call-by-need and call-by-value strategies as particular concurrent sc... | BAC | ABC | CAB | BAC | Selection 2 |
**A**: The bars and polyline correspond to the left and right Y-axes, respectively**B**:
Figure 13: The comparison of cloud-side computational efficiency between FairCMS-I and FairCMS-II**C**: The time consumed by FairCMS-II is 100 times the reading on the Y-axis. (a) Efficiency comparison under different number of us... | ACB | BAC | CAB | CAB | Selection 2 |
**A**: (2020) uses a logarithmic neural network to adaptively learn high-order feature interactions, and SIGN Su et al. (2020) utilizes mutual information to detect beneficial feature interactions and a linear aggregation strategy to model them. However, these approaches may not be expressive or interpretable enough.
*... | BAC | ACB | CBA | ACB | Selection 3 |
**A**: Self-concordant functions have received strong interest in recent years due to the attractive properties that they allow to prove for many statistical estimation settings [Marteau-Ferey et al., 2019, Ostrovskii & Bach, 2021]. The original definition of self-concordance has been expanded and generalized since its... | ACB | BCA | ABC | CAB | Selection 3 |
**A**: However, to be considered an efficient approximation algorithm in theory, ideally the dependence on all relevant parameters should be polynomial**B**: The question whether there is a (1+ε)1𝜀(1+\varepsilon)( 1 + italic_ε )-approximate matching algorithm for general graphs with poly(1/ε)poly1𝜀\operatorname{poly... | ACB | BAC | BCA | ABC | Selection 1 |
**A**: In this paper, we consider decentralized optimization over general directed networks and propose a novel Compressed Push-Pull method (CPP) that combines Push-Pull/𝒜ℬ𝒜ℬ\mathcal{A}\mathcal{B}caligraphic_A caligraphic_B with a general class of unbiased compression operators**B**: CPP enjoys large flexibility in ... | ABC | BAC | CBA | CBA | Selection 1 |
**A**:
We develop multiple novel algorithms to solve decentralized personalized federated saddle-point problems**B**: In addition, we present Algorithm 3 which used the randomized local method from [30]. This algorithm is used to compare Algorithm 1 with Local randomized methods (like Algorithm 3) in practice.**C**: T... | CAB | CAB | CAB | ACB | Selection 4 |
**A**: CEs exist in a convex polytope, so any convex function can select among them. Maximum entropy correlated equilibrium (MECE) (Ortiz et al., 2007) is limited to full-support solutions, which may not exist when ϵ=0italic-ϵ0\epsilon=0italic_ϵ = 0, and can be hard to solve in practice. Therefore, there is a gap in th... | CBA | CAB | BAC | ACB | Selection 1 |
**A**: This work was supported in part by a gift to the McCourt School of Public Policy and Georgetown University, Simons Foundation Collaboration 733792, Israel Science Foundation (ISF) grant 2861/20, and a grant from the Israeli Council for Higher Education**B**: Part this work was completed while Ligett was visiting... | BCA | ABC | CBA | ACB | Selection 4 |
**A**: This body of work gives a good theoretical understanding of polynomial-time data compression for NP-hard problems.
**B**: It includes deep techniques for obtaining kernelization algorithms [10, 28, 39, 43], as well as tools for ruling out the existence of small kernelizations [11, 19, 23, 30, 32] under complexit... | BAC | CBA | ABC | BCA | Selection 2 |
**A**: However, collecting the dataset like [70] calls for capturing the same scene with a fixed camera for a long time, which is hard to be realized in practice. To obtain the foregrounds in different capture conditions, Song et al**B**: [140] proposed an interesting way to construct GMS Dataset. Specifically, they pl... | CBA | BCA | CBA | CBA | Selection 2 |
**A**: 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 the long run. To achieve this, we divide the city into uniform hexagonal grids, as opposed to square grids used in previous studies [21, 6].
**B**... | ACB | CBA | BCA | CAB | Selection 2 |
**A**: Using more data to train the underlying models, thereby obtaining better predictions, will lead to tighter prediction intervals as long as the calibration set is not too small. This conclusion is in line with the observations from Figs. 1 and 2. This experiment was then repeated in an extreme fashion, where the ... | BAC | CAB | ABC | BCA | Selection 4 |
**A**: For fine-tuning, we create training, validation and test splits for each of the three datasets of the downstream tasks with the 8:1:1 ratio at the piece level (i.e., all the 512-token sequences from the same piece are in the same split).
With the same batch size of 12, we fine-tune the pre-trained our model for ... | ACB | ABC | ACB | ACB | Selection 2 |
**A**: This description draws a comparison e.g**B**: to L(k,1)𝐿𝑘1L(k,1)italic_L ( italic_k , 1 )-labeling problem (see e.g**C**: [10] for a survey), where the colors of any two adjacent vertices have to differ by at least k𝑘kitalic_k and the colors of any two vertices within distance 2222 have to be distinct.
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**A**: Learning (ICML), Pittsburgh, USA, Jun. 2006, pp. 369–376.**B**:
A. Graves, S. Fernández, F. Gomez, and J. Schmidhuber, “Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks,” in Proc. 23rd Int**C**: Conf. Mach | ABC | CBA | CAB | ABC | Selection 3 |
**A**: Most 2D WSSS methods use image-level labels**B**: Based on class activation map(CAM)[12], many methods[28, 29, 30, 31, 31, 32, 33, 17, 18, 19] refines the CAM generated from a classification network to generate pseudo-pixel-level labels**C**: Then, segmentation networks are trained using the pseudo-pixel-level l... | BCA | BAC | ABC | BAC | Selection 3 |
**A**: Compared with the methods with LiDAR and stereo sensors, 3D object detection with monocular images is challenging due to the absence of reliable depth information**B**: In contrast to these methods, we only use the monocular image as input without any extra burden.**C**: Existing works [6, 28, 26, 25, 5, 10] hav... | CBA | CBA | ABC | ACB | Selection 4 |
**A**: It contains 1,255 training images and 300 testing images.
CTW1500 [18] consists of curved and multi-oriented texts, all annotated by polygons, and tends to label long curved text**B**: It has 1,500 training and 1,000 testing images.**C**: Total-Text [19] consists of horizontal, multi-oriented, and curved text in... | BCA | BAC | ACB | CAB | Selection 1 |
**A**:
In this section, we evaluate the performance of the proposed methods 111https://github.com/chenjie20/IPStatistics on three synthetic datasets that contain 5 million, 10 million, and 50 million randomly generated IP records**B**: Each individual IP address contains one or more of IP records**C**: The average num... | ABC | CBA | ACB | ACB | Selection 1 |
**A**: The above 3333-by-3333 block linear problems (1) and (2) can be naturally extended to the n𝑛nitalic_n-tuple cases**B**: When
the system matrix in (2) is extended to the n𝑛nitalic_n-tuple case, it corresponds to the linear system resulting from the domain decomposition method for elliptic**C**: For example, whe... | BAC | BCA | ACB | BCA | Selection 3 |
**A**: By waiting for several training iterations to exchange this information, the communication cost of the algorithm is reduced.
Our approach is thus a communication efficient combination of learning with both vertically and horizontally partitioned data in a multi-tiered network.**B**: The hubs orchestrate this inf... | CBA | CAB | ACB | ACB | Selection 1 |
**A**: In these systems, the states, inputs, and outputs are tensors. It would be interesting to explore multilinear time-invariant systems that depend on tensor-tensor multiplication and investigate their applications, leaving this as a topic for future research.**B**: The study of pseudospectra for T-eigenvalues of t... | BCA | ABC | ACB | CBA | Selection 4 |
**A**:
As with most computer vision problems, image inpainting has been largely advanced by the widespread use of deep learning during the past decade**B**: There also exists another trend to combine the advantages of deep generative and traditional patch-based methods for image inpainting [35, 30, 24, 15], delivering... | ACB | ABC | CBA | CBA | 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... | ACB | CAB | BAC | CBA | Selection 3 |
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