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A: We also observe evidence of out-of-distribution generalization.B: We propose Subgoal Search method with two implementations: MCTS-kSubS, BF-kSubSC: We demonstrate that our approach requires a relatively little search or, equivalently, is able to handle bigger problems	ACB	ABC	CAB	CBA	Selection 3
A: Standard precision, recall and, F1 scores are calculated as evaluation metrics to show the performance of different model settingsB: We conduct experiments on our substitution dataset and three general datasets to verify our method from different perspectivesC: In this paper, we set up experiments on Pyt...	BAC	ABC	CAB	CAB	Selection 1
A: We evaluated the neural étendue expanders using a prototype holographic displayB: See Supplementary Notes 9 and 10 for details. C: The prototype consists of a HOLOEYE-PLUTO SLM, a 4F system, a DC block, and a camera for imaging the étendue expanded holograms	ABC	ACB	BCA	CAB	Selection 2
A: Table 2B: ‘W’, ‘S’, ‘D’, and ‘O’ in the four rightmost columns represent the word-level, sentence-level, and document-level tasks, and tasks of other abstract levels such as RE, respectively. A single checkmark could mean joint learning of multiple tasks of the same type. The ‘Architecture’ column denotes t...	BAC	ABC	ACB	BCA	Selection 3
A: Be sure to use the \\\backslash\IEEEmembership command to identify IEEE membership status. Please see the “IEEEtran_HOWTO.pdf” for specific information on coding authors for Conferences and Computer Society publicationsB: Note that the closing curly brace for the author group comes at the end of the thanks g...	BCA	ABC	BCA	CAB	Selection 2
A: Furthermore, w(i,β)subscript𝑤𝑖𝛽w_{(i,\beta)}italic_w start_POSTSUBSCRIPT ( italic_i , italic_β ) end_POSTSUBSCRIPT isB: But then, exactly one of w(i,β),w(i′,β)subscript𝑤𝑖𝛽subscript𝑤superscript𝑖′𝛽w_{(i,\beta)},w_{(i^{\prime},\beta)}italic_w start_POSTSUBSCRIPT ( italic_i , italic_β ) end_POSTSUBSCRIP...	BCA	BCA	BAC	CBA	Selection 4
A: Links, on the other hand, exhibit an additional differential dynamic. Although there is a strong initial boost from the treatment intervention, decay in the number of links actually appears to accelerate mildly relative to groups in the baseline sessions. B: A natural question is how contributions and averag...	BAC	BAC	ACB	CAB	Selection 4
A: Currently, most DL-based SISR models can only be applied to one or a limited number of multiple upsampling factorsB: Therefore, it is necessary to develop a flexible and universal scale arbitrary SISR model that can be adapted to any scale, including asymmetric and non-integer scale factors. Although a few s...	ACB	BAC	BCA	CAB	Selection 3
A: For blind super-resolution, Neural Knitwork core module is utilized with adjusted losses as illustrated in Figure 5. The queried coordinates for a patch network include all super-resolved coordinates, which means that it is not possible to compute the patch reconstruction loss in this modeB: To perform sup...	ACB	ABC	BAC	CAB	Selection 3
A: The effect of approximation of the posterior on the performance of TS is an area of increasing interest, as Phan et al., (2019) have recently proved that a small constant approximation error can induce linear regret in the application of TS to certain simple multi-armed bandit problems. Appropriately designed ap...	CBA	BCA	CAB	CAB	Selection 1
A: Here we extend our initial proposal to accommodate transformers, and to improve the applicability and scalability of this approachB: Our approach could be described as learning from textual descriptions, and it resembles certain human learning processes [15, 16]: comprehending the text and incorporating the...	ACB	BAC	BCA	CBA	Selection 1
A: As a simple example, consider an algorithmic trading scheme using a predictive model for stock returns, which will use the output of the predictive model together with the rule “place a sell order if the 90% quantile of the predictive stock return distribution exceeds 10% three days in a row”. Or a traffic offic...	ACB	CAB	CBA	ABC	Selection 2
A: Recall that elementary doctrines can be understood as those primary doctrine endowed with equality predicatesB: replacing of ∧,⊤top\wedge,\top∧ , ⊤ by ∗,κ∗𝜅\ast,\kappa∗ , italic_κ).C: The following definition introduces those primary linear doctrines that are elementary as a direct linearisation of Def...	CAB	ACB	BAC	ABC	Selection 2
A: Trivially, ForestSim obeys Range (P1) and Symmetry (P2)B: It has been proved that Transitive similarity (P4) is implied by Triangle inequality (P5) [5]C: Thus, we only need to prove that ForestSim satisfies Automorphism conformation (P3) and Triangle inequality (P5).	BAC	BAC	ABC	BAC	Selection 3
A: Some researchers have formulated tasks aimed at modeling implicit sentiments and opinions. For instance, Cai et alB: (2021) proposed a quadruple extraction task (aspect, category, opinion, and sentiment), while Murtadha et al. (2022) proposed a unified framework that crafts auxiliary sentences to aid implici...	ACB	BAC	ABC	BCA	Selection 4
A: This process is somewhat elaborate and the reader is referred to [31] and [32] for all of the detailsB: The operator 𝐋𝐋\mathbf{L}bold_L and 𝐖𝐖\mathbf{W}bold_W are constructed from a multilevel decomposition of the location of predictorsC: However, for the exposition in this section it sufficient to k...	BAC	ACB	CAB	CBA	Selection 1
A: The QNN consists of multiple blocks. Each has three components: encoder encodes the classical values to quantum states with rotation gates such as RY; trainable quantum layers contain parameterized gates that can be trained to perform certain ML tasks; measurement part measures each qubit and obtains a classical...	CAB	BAC	ACB	BCA	Selection 4
A: If the cosine distances among a set of hypotheses are close to zero, they are considered to be parallel with each otherB: After that, each representative model hypothesis is a unique event trajectory, and it is not parallel with the other representative hypotheses.C: Then, for each parallel hypothesis s...	CAB	ACB	CBA	CBA	Selection 2
A: This research was partially financed by the French government IDEX-ISITE initiative 16-IDEX-0001 (CAP 20-25) and by the ANR project GRALMECO (ANR-21-CE48-0004)B: In particular, we thank Giacomo Kahn and Armen Petrossian for preliminary discussions. We also thank the referees for their comments that helped i...	CAB	CBA	ACB	BCA	Selection 3
A: Follow the linear evaluation protocols in Sec. V-B, we compare the existing relation-based KD methods including RKD [65], PKT [64], SP [66], SSKD [68], CRD [69], and SEED [67]. We adopt the BCE loss for GenURL in the KD task. B: We choose multiple smaller networks with fewer parameters as the student network...	ABC	BCA	CBA	BCA	Selection 3
A: The reduced peak memory also allows larger freedom when designing the backbone architecture (e.g., using a larger input resolution)B: To explore such a large design space, we propose to jointly optimize the neural architecture and the inference scheduling in an automated manner.C: Redistributing the rec...	BAC	CBA	BCA	CAB	Selection 3
A: The ICDM 2020 Knowledge Graph Contest competition provides 500 recent articles444http://biendata.xyz/media/dataset.zip from Instagram which is selected by industry-solution experts to ensure the language formality, diversity, and depth of knowledge in terms of real-world applications. In addition, the competitio...	ACB	CAB	ABC	BAC	Selection 1
A: Data augmentation has achieved great success in image data where the invariance of various views (e.g., color-invariant, rotation-invariant, and resizing-invariant) are well-understood [3, 31]B: However, due to the complex structural information and the coupling between nodes in the graph, the changes induc...	CAB	CAB	CBA	ABC	Selection 4
A: We see interesting dynamics in topographic similarity distribution with respect to change in the noise levels. Namely, it starts by accumulating mass at the higher spectrum of its values, reaching a peak for noise 0.10.10.10.1, after which it transitions to a bimodal distribution, finally shifting its mass more ...	ACB	BCA	BCA	CBA	Selection 4
A: As opposed to these works, we make use of safe expert demonstrations. Expert trajectories are utilized in [51] to learn a contraction metric along with a tracking controller, while motion primitives are learned from expert demonstrations in [52]. In our previous work [53], we proposed to learn CBFs for known non...	BCA	CBA	ABC	ACB	Selection 2
A: Aaronson and Ambainis [AA14] showed that this related conjecture implies 13. it remains open to this day. Theorem 12 could be seen as the analogue of 13 for sparse oracles—an analogue that, because of the sparseness, turns out to be much easier to prove.B: While 13 has become influential in Fourier analysis...	CBA	CAB	BCA	BAC	Selection 2
A: When DCDFM degenerates to DCSBM, our results also match classical results under DCSBM. Numerical results of both simulated and real-world networks show the advantage of introducing node heterogeneity to model weighted networks.B: (b) To fit DCDFM, an efficient spectral clustering algorithm called nDFA is de...	CAB	CBA	ACB	ACB	Selection 1
A: Extensions of QMIX include MAVEN Mahajan et al. (2019), COMIX de Witt et alB: Following this idea, Rashid et al. (2018) introduced QMIX, which learns a complex state-dependent decomposition by using monotonic mixing hypernetworksC: (2020), SMIX(λ𝜆\lambdaitalic_λ) Wen et al. (2020), and QTRAN Son	BAC	CBA	ACB	ACB	Selection 1
A: Since domain experts may have knowledge and ideas based on years of research and study that current ML models do not make use of, the facilitation of communication between ML models and humans is a primary design goal.B: G4: Reason about the relationship of certain features and knowledge acquired. Unlike G2,...	ABC	BCA	CAB	CBA	Selection 3
A: To the best of our knowledge, the current paper is the first to exploit polarization reconfigurable HS - MIMO spatial multiplexing (PR-HS-MIMO), which significantly outperforms that of the conventional HS-MIMO systems with comparable complexity. B: On the other hand, polarization diversity is not taken into ...	BCA	BCA	CBA	CAB	Selection 4
A: The main contribution of this paper is to show that surprisingly this conjecture is false.B: Then the density of the piece in its axis-parallel bounding box is at least 1/2121/21 / 2, and the algorithm for rectangles can be applied to the bounding box, again leading to O⁢(1)𝑂1O(1)italic_O ( 1 )-competitive ...	BAC	CAB	BCA	ABC	Selection 2
A: Therefore, it is of interest to know how the proposed similarity is correlated with MREB: Figure 6 presents such a plot, which nicely shows a strong (negative) correlation coefficient of −0.6750.675-0.675- 0.675. This enables us to utilize the proposed similarity function as a proxy of MRE, which is more con...	ACB	BCA	CAB	ABC	Selection 2
A: We see that DFSP returns larger fuzzy weighted modularity than its competitors except for the Karate-club-weighted network. Meanwhile, according to the fuzzy weighted modularity of DFSP in Table 3, we also find that Gahuku-Gama subtribes, Karate-club-weighted, Slovene Parliamentary Party, Les Misérables, and Pol...	ACB	CBA	BCA	BAC	Selection 4
A: They find that preventing representations to be overly compressed can improve DML generalizationB: They achieve this by randomly switching negative samples with positive samples in the ranking loss. Differently, our work focuses on CIL, and propose to use class-wise feature decorrelation, which is a more eff...	BCA	BAC	CAB	CAB	Selection 1
A: In both phases, the network was trained with the GradICON’s default hyperparameters (i.e., learning rate of 5⁢e−55superscript𝑒55e^{-5}5 italic_e start_POSTSUPERSCRIPT - 5 end_POSTSUPERSCRIPT, regularizer weight λ=1.5𝜆1.5\lambda=1.5italic_λ = 1.5, and ADAM optimizer)B: Due to memory limitations, a batch si...	ABC	ACB	CBA	BCA	Selection 1
A: For Question 1, we provide a definitive answerB: For Question 2, we establish results that form crucial steps towards a definitive answer. As we explain, an answer to Question 2 will resolve a challenging graph-theoretic open problem. Our contributions can be summarized as follows:C: Our goal is to prov...	BCA	CAB	CBA	ACB	Selection 1
A: In Figure 12(d), we see that there are more bridging nodes with the large node-absorption rate δ∗∗subscript𝛿absent\delta_{}italic_δ start_POSTSUBSCRIPT ∗ ∗ end_POSTSUBSCRIPT in the final stage than in the peak-duration stageB**: Specifically, in stage 68 (unlike in stage 29), the disease can disappear more ...	ACB	BAC	ABC	BAC	Selection 1
A: In our overall methodology, to conserve node and link resources, we post-process or ”throttle” the swapping-tree obtained from the DP algorithm by increasing the generation latencies of some of the non-root nodes such that (i) the latencies of siblings are equalized, and (ii) the parents latency is related to th...	CBA	CBA	BCA	ABC	Selection 4
A: Their subsequent study also confirms that driving explanations can help mitigate the negative impact of AVs failures on users [150]. Finally, Kim et al.’s user study [151] confirms that humans do not need explanations seamlessly, and presenting explanations only in critical driving conditions is preferred to enj...	BCA	CBA	ABC	ACB	Selection 2
A: Inspired by basic Ghost modules in the GhostNet [7], we design the lightweight neural network named GhostCNN for front-ended feature extraction. Ghost modules skillfully utilize linear transformations to generate ghost feature map pair examples to reduce the computational cost significantly and ensure a satisfac...	CBA	BAC	CAB	ABC	Selection 1
A: The computation of this work has been obtained thanks to Magma [6] and to the server of the Laboratory of Cryptography of the Department of Mathematics, University of TrentoB: AcknowledgementC: The results in this paper appear partially in the MSc thesis of the second author, who thanks his supervisors (...	BAC	CBA	CBA	CBA	Selection 1
A: Opponent modeling requires building a model from previous data or actions observed during an online playB: Model exploitation is finding a good strategy against the given model and is the main focus of this paper. In smaller games, we can trivially compute a best response to exploit the opponent maximally, o...	BAC	ACB	ABC	BCA	Selection 4
A: The greedy amalgamating algorithm to yield a good η𝜂\etaitalic_η-fat partition is essentially a greedy algorithm for numbers, and we describe that firstB: The main step in the number greedy algorithm involves bipartitions, and the following well known problem.C: To prove Lemma 3.1, it of course suffice...	ABC	ABC	BCA	ACB	Selection 3
A: Future research could profit from our work by exploring the average effect of specific environmental shocks, such as droughts or floods, and the important role of mediating factors that influence the decision to migrate, such as specific economic and social conditions.B: If a key function of meta-analysis i...	BCA	CAB	BAC	BCA	Selection 2
A: To handle multiple performance requirements, they deploy a two-layer algorithm for each player, demonstrating that the overall algorithm enjoys favorable regret guarantees. A vital component in their algorithm is to facilitate collaborations between the meta and base layersB: This is again achieved by inject...	BCA	CBA	CAB	ACB	Selection 1
A: The integer n𝑛nitalic_n is called a period of x𝑥xitalic_xB: For a nonempty word w𝑤witalic_w, we let wωsuperscript𝑤𝜔w^{\omega}italic_w start_POSTSUPERSCRIPT italic_ω end_POSTSUPERSCRIPT denote the right-infiniteC: A sequence x∈Aℤ𝑥superscript𝐴ℤx\in A^{\mathbb{Z}}italic_x ∈ italic_A start_POSTSUPERSC...	BAC	BCA	CAB	CBA	Selection 2
A: (2017)B: More precisely, these authors established the third term on the right-hand side inC: The result in Theorem 4 for s≥1/2𝑠12s\geq 1/2italic_s ≥ 1 / 2 (that is, 2⁢k+2≥d2𝑘2𝑑2k+2\geq d2 italic_k + 2 ≥ italic_d) was already derived in Sadhanala et al	CBA	BCA	ACB	BAC	Selection 2
A: In Wang et al. (2017), persistent homology was shown to outperform topographic power maps. In (Yoo et al., 2017), center persistency was shown to outperform the network-based statistic and element-wise multiple corrections. In Chung et al. (2023b), persistent homology based clustering is shown to outperform k𝑘k...	CBA	CAB	BCA	CAB	Selection 1
A: according to Corollary 4, fs⁢(θ,τ)=0subscript𝑓𝑠𝜃𝜏0f_{s}(\theta,\tau)=0italic_f start_POSTSUBSCRIPT italic_s end_POSTSUBSCRIPT ( italic_θ , italic_τ ) = 0 has no solution for τ∈(0,τm)𝜏0subscript𝜏𝑚\tau\in(0,\tau_{m})italic_τ ∈ ( 0 , italic_τ start_POSTSUBSCRIPT italic_m end_POSTSUBSCRIPT ) and has a solutio...	ABC	ACB	CAB	ABC	Selection 2
A: Let us also consider the unsafe set for this system to be (12) and the metric measuring the distance from this unsafe set to be given by (13)B: If the controller gains are chosen such that the following inequalities are satisfied,C: Consider the system (4) with boundary conditions (8)	BCA	ACB	CBA	ACB	Selection 1
A: Therefore, evaluating interruptibility has significant value to companies in terms of cost and time. To continuously measure a person’s interruptibility, Zuger et alB: [39] study 13 software engineers over two weeks using wearable sensors in addition to keyboard and mouse interaction data. The ground truth i...	BCA	ABC	ACB	ABC	Selection 1
A: Collecting Training Samples. Recall that a sample in PU-Setting is comprised of a sample of PUs’ parameters (location and power) and the optimal power allocated to the SUB: First, we compute an FFT on the I/Q samples collected within a time window to get a power spectral density (PSD) plot. Then, we compute ...	ABC	CBA	ACB	ABC	Selection 3
A: Section 2 contains preliminaries and is split in the following subsectionsB: In Section 2.1, after reviewing the definitions of groups and group actions, we define the notions of congruence and symmetry of curves relative to a given group. In Sections 2.2 and 2.3, we follow [12] to define Euclidean and affi...	ABC	CAB	BAC	BCA	Selection 4
A: On the other hand, the use of an irregular order is then considered by researchers to accelerate convergence. Particularly, it is shown in [31] that randomization leads to faster convergence in terms of expectationB: Obviously, this is not guaranteed for each instance of the algorithm. The Gauss-Southwell me...	BCA	BAC	CBA	CBA	Selection 1
A: The ability to tune integration constants is fundamental for neuromorphic applications, as spike rates vary between different applicationsB: Tables I and II show that different pulse settings (Voltage and duration) give rise to different decay time constantsC: While these results do not enable us to mod...	CAB	CBA	BAC	CBA	Selection 3
A: In this paper we study an agent-based model for opinion formation on a social network where the opinion of an agent depends both on its own intrinsic opinion and on the opinions of its network neighborsB: One of the earliest influential models in this direction was defined by DeGroot DeGroot (1974)C: In...	ACB	ABC	CBA	CBA	Selection 2
A: Deep learning models should not be considered as a replacement for clinical diagnosis by medical professionalsB: It is also crucial to validate the accuracy and reliability of these models on diverse and representative datasets. Interpretability and explainability of deep learning models in medical imaging ...	CBA	ACB	BAC	CAB	Selection 2
A: Our results offer analytical innovation by establishing foundational principles for a formal analysis that yields exact solutions in dynamic programmingB: We demonstrate several instances in which it is feasible to perform exact analyses of dynamic programming regardless of the need to project the evolution...	BCA	CBA	ACB	BCA	Selection 3
A: In contrast, the latent code of a classical autoencoder exhibits multiple clusters for different orientations of the same digit class. B: For all other rotations, we see slight variations in the latent code, which, however, is to be expected due to interpolation artifacts for rotations on a discretized grid*...	ABC	BCA	ABC	CAB	Selection 4
A: Given the relatively small difference in performance between the GP models and the best random baseline one might be tempted to ask whether the extra effort needed for the former is justified. Therefore, it is worth keeping in mind the applicationB: When deployed, each extra iteration will mean one extra se...	ABC	CAB	ACB	BAC	Selection 1
A: Test data bounds are reported in Table 4. B: We report the average ELBO (±1plus-or-minus1\pm 1± 1 standard error) on the training set after 1M steps over 5 independent runsC: Training binary latent VAEs with K=2,3𝐾23K=2,3italic_K = 2 , 3 (except for RELAX which uses 3333 evaluations) on MNIST, Fashion-...	CBA	BAC	ABC	ABC	Selection 1
A: This is complemented by both analytical results and corresponding simulations. In Section VI, we discuss the deficiencies of the Random selection approach and the challenges wrtB: its practical implementation.C: Then, in Section V we consider different receiver processing techniques and provide their tho...	ACB	BCA	CBA	ACB	Selection 2
A: Moreover, the exponent 3333 in our theorem is sharp and can not be lowered; see Section 5.4.B: In fact, in our algorithm, the yielded path has length at most (300)9/2⁢log⁡300superscript30092300(300)^{9/2}\log{300}( 300 ) start_POSTSUPERSCRIPT 9 / 2 end_POSTSUPERSCRIPT roman_log 300 times the length of the sm...	CAB	CBA	CAB	ABC	Selection 2
A: Section 3 is on the computation of the Chow form in ℙnsuperscriptℙ𝑛\mathbb{P}^{n}blackboard_P start_POSTSUPERSCRIPT italic_n end_POSTSUPERSCRIPT and the extension of techniques to compute Hurwitz formsB: In section 2 we present a short overview of Chow formsC: Section 4 presents algorithms for computing...	CAB	CBA	ACB	BAC	Selection 4
A: Deepspectrum-Resnet50, Deepspectrum-VGG19, and VGGishB: They correspond to the six feature sets described in the Data Processing and Cleaning section for Speech SignalsC: Each folder includes a CSV file per audiovisual stimuli and volunteer. Each CSV has as many columns as the number of features calculat...	CBA	BCA	CBA	ABC	Selection 4
A: However, this does not prevent an adversary from designing new attack algorithms. An adversary can exploit the limitation of these defenses by continually crafting new attack algorithms and evading the classifier. As a result, an arms race has started in adversarial malware detection. Figure 2 shows a schematic ...	ACB	CAB	ACB	CBA	Selection 2
A: Almost surely either a player was chosen on Step 1 or 2 or the sum of just the odd-numbered terms (given by B’s moves) of expression (2) diverges to ∞\infty∞, by Lemma 3.6B: In the latter case, the sum of the even-numbered terms must diverge to −∞-\infty- ∞ (as the sum of all terms is convergent), and theref...	CAB	BCA	ACB	ABC	Selection 4
A: Among the physical-world ones, object texture is the most popular (half of the all attacks)B: Status and trends. As shown in Table I, existing works predominantly adopt physical-layer attack vectors, with 63.0% and 27.8% using physical-world and sensor attack vectors, respectivelyC: This is likely becaus...	CBA	ACB	ACB	BAC	Selection 4
A: in [2], where they extend the result of the first paper by proving that Maximum Cut is NP-complete on graphs of interval count four. Using the technique of the above work, de Figueiredo et alB: prove the NP-completeness of Maximum Cut on permutation graphs as well, which too was open for a long time [11].**C...	ABC	ABC	CAB	BCA	Selection 4
A: We confirm our findings on similar, natural-video datasets (H.4) and other BN variants (H.5). Then, we discuss how freezing layers can alleviate BN-issues (H.6) and position our proposed models within the state of the art for surgical phase recognition (H.7). We show BN’s potential to cheat (H.8), provide eviden...	CBA	ACB	BCA	BCA	Selection 1
A: Classification Loss. Early indirect optimization methods include softmax loss[1, 21, 30], which uses the similarity between the deep feature and class weight vectors. Softmax loss has been widely applied in classification problems, but it is not appropriate for FR because testing is done by similarity compariso...	BCA	ABC	CAB	BCA	Selection 2
A: Such an approach performs data augmentation by competitively creating new samples, i.e., a generator attempts to create synthetic images to fool the discriminator, which then tries to identify whether they are fake or realB: A promising solution to generate synthetic images lies in the Generative Adversaria...	CAB	ABC	ACB	BAC	Selection 4
A: RAF-DB contains 29672 facial images downloaded from the InternetB: In experiments, we use the basic database including 12,271 training and 3,068 testing images. C: For the RAF-DB dataset, the facial landmarks are manually annotated via the crowdsourcing method with basic or compound expressions	CAB	CAB	CBA	ACB	Selection 4
A: These rating points are somewhat analogous to poker chips: when player A𝐴Aitalic_A and player B𝐵Bitalic_B play a game, they each place some of their rating points into a potB: In the case of a draw, the players split the pot evenly. If one player wins, they take the entire pot. The heart of the Elo system ...	CAB	BCA	BAC	CBA	Selection 2
A: The doctors need explanations, and the minority class in this binary classification problem is of more importance than the majority consisting of healthy patients. In reality, patients who are healthy but predicted as ill will undergo extensive follow-up diagnostic tests before treatments such as surgery and che...	CBA	ABC	BAC	ACB	Selection 1
A: As we discussed before, on Ethereum, the chance of transactions being frontrun is a bit higher on account of higher volatility (we theorize, due to NFT transactions and slower block confirmation time) compared to BSC, which is more stable on account of the faster settling of transactionsB: Each Ethereum bloc...	ABC	CAB	ACB	BAC	Selection 3
A: In this section, we define the policy gradient, the gradient of the equilibrium policy value with respect to the selection criterion, give an estimator of the policy gradient, and use the estimator to learn policiesB: (2021); Wager and Xu (2021) and use gradient-based optimization with policy gradient estim...	ACB	BAC	ABC	BAC	Selection 1
A: For each dataset, we tune ResNet-18 and OccamResNet-18 separately. B: The hyperparameter search grids for OccamResNet-18 and all of the comparison methods are shown belowC: In Table A14, we present the details about optimizers, training epochs and other hyperparameters for each method on each dataset	BCA	ACB	ACB	CBA	Selection 4
A: The former refers to the contexts within the same video frame or the contexts of unchanged content across the neighboring frames. Image semantic segmentation has exploited such contexts (for images) a lot, mainly accounting for multi-scale [27, 28, 30, 24] and global/long-range information [29, 18, 31, 32]B:...	CAB	BAC	BCA	CAB	Selection 2
A: Prior studies have used an offline profiler [10, 11] to identify frequently-accessed embeddings. Some of these studies do not account for this overhead, up to 15%, in their training times [10]B: As user behavior changes rapidly every few hours or days, static profiling may not quickly identify the correspond...	BAC	ACB	CBA	CAB	Selection 2
A: Indeed, Theorem 3 allows us to extend [6, LemB: 4.13], which applies only to polytopal complexes, to all polyhedral complexes imbedded in ℝnsuperscriptℝ𝑛\mathbb{R}^{n}blackboard_R start_POSTSUPERSCRIPT italic_n end_POSTSUPERSCRIPT equipped with the standard PL structure. C: While we believe the above re...	ACB	BCA	BAC	BAC	Selection 2
A: Later developments in this direction can be found in [16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26].B: Among these successful applications in physical sciences, the more challenging task is to use neural networks to study nonequilibrium problemsC: Recently, an algorithm of artificial neural networks was p...	BAC	ABC	CAB	BCA	Selection 3
A: starting atB: First we generate analytic solutions of the equationC: In this section, we carry out a 3D error test with the following form of solutions on the domain Ω=[0,1]3Ωsuperscript013\Omega=[0,1]^{3}roman_Ω = [ 0 , 1 ] start_POSTSUPERSCRIPT 3 end_POSTSUPERSCRIPT	BAC	ACB	CBA	CAB	Selection 3
A: Since the RU measures are model-independent, we perform the effectiveness validation experiments for both classification and regression tasksB: For the classification tasks, we use SYN, DCC, AD, RS and GS data sets, and for the regression tasks, we employ RN, HS and DI data setsC: To demonstrate the effe...	ABC	BCA	ACB	ACB	Selection 1
A: Through their interaction with CO-oPS, they explicitly brought up the app names that could be a concern and discussed how these apps may harm their teensB: The rest of the parents (37%, N=7) identified some potentially concerning apps that they already knew that their teens had been usingC: They mostly ...	BAC	ABC	CAB	ABC	Selection 1
A: Persistence diagrams are stable against certain perturbations of the filtrationB: This can be made precise using two similarity measures: the interleaving distance for filtrations and the bottleneck distance for persistence diagramsC: Both similarity measures are symmetric and satisfy the triangle inequ...	ABC	CAB	ACB	BCA	Selection 1
A: Our causal inference framework not only fundamentally explains how subject-specific AU semantic relations hurt the performance of AU recognition models, but also provides a solution by removing the effect caused by confounder SubjectB: To this end, we formulate subject variation problem by constructing a ca...	BAC	ABC	ACB	BCA	Selection 1
A: While the basic BBP scheme can achieve scalability in theory, its applicability in real blockchain systems, e.g., Ethereum, needs further discussionB: The results highlight both the prospects and technical challenges in designing a practical BBP scheme for Ethereum. C: This section delves into experimen...	CBA	ABC	BCA	ACB	Selection 4
A: In a broader context of reinforcement learning with partial observability, our work is related to several recent works on POMDPs with special structures. For example, Kwon et alB: (2021) considers POMDPs having tree-structured states with their positions in certain partitions being the observations. Compare...	BCA	BAC	BAC	ACB	Selection 4
A: However, high weightage was attributed to authors publishing more articles. In addition, to find the list of most impactful authors, their collaborating links were also considered, along with the number of published documents. The top ten most impactful authors are listed in the Table 1 B: The most significa...	BCA	CAB	CBA	ABC	Selection 1
A: We provide the results in the Appendix E.2. B: In this regard, we find that for each of the 8 datasets and each of the communities in the dataset, the intra-community compression ratio is higher than the inter-community compression ratioC: This provides an average measurement of the compression ratio in ...	BCA	CAB	CAB	CBA	Selection 4
A: It is reasonable to expect the performance drop under the task setting with incomplete visual inputB: To tackle the problem, we propose to supplement the missing visual data from another information source: the natural language dialog. Intuitively, humans rely on the multi-sensory systems from various modali...	ABC	CBA	CAB	BCA	Selection 4
A: [8] depicts state of the artB: The recent survey by Chan et alC: Here, we mention some of the models: obnoxious facility games where every agent wants to stay away from the facility [11, 13]; heterogeneous facility games where the acceptable set of facilities for each agent could be different [25, 17, 12...	BAC	ABC	ACB	CBA	Selection 1
A: In consequence, the vertices of the edge link triangle in the chain should have different colorsB: All other edges of the chain form part of some induced paw and their incident vertices have degree odd in such paw. Therefore, every pair of consecutive vertices in the chain have different colors in any valid ...	ABC	ABC	BAC	BCA	Selection 4
A: If the simplicial partition-based implementation is considered, then one has also to account for the complexity of the resulting invariant set, which is typically high 6, 8, 49, 10, 2, 9. These methods can therefore require significant memory to store the vectors and/or matrices describing every simplicial parti...	BCA	BAC	ACB	CAB	Selection 4
A: Averaged over the first 20 sequences of the test set, the overfitted baseline achieves an IoU of 0.540.540.540.54 while our method achieves a score of 0.760.760.760.76B: For a quantitative evaluation of the prediction quality, we report the intersection over union (IoU) averaged over all frames of the test ...	ACB	BAC	BCA	ABC	Selection 2
A: Thus, rather than merely transmitting raw data in compressed quantum states, the QSC framework intelligently extracts semantic information from the data. It then transmits only the essential quantum semantic representations over quantum channels, thereby resulting in more resource-efficient QCNs while maintainin...	BCA	ABC	BAC	ACB	Selection 1
A: In particular, since the adopted multiple access scheme is based on time-division multiple access (TDMA), the resource optimization must deal with routing paths and scheduling of directional transmissions along established links. B: Therefore, a proper radio resource allocation is essential to efficiently op...	CBA	ABC	ACB	BCA	Selection 1
A: Case 1: small profitB: In this case, agents of type θ=0𝜃0\theta=0italic_θ = 0 would choose not to run trials, since their expected profit for running a trial is -$5 million. Hence, all approved drugs would be effective drugs. C: Suppose that companies who receive approval make $100 million in profit, 10...	ACB	BAC	BCA	CBA	Selection 1
A: Finally, PPIR for point cloud data is released in a separated repository555https://github.com/rtaiello/ppir_pc.B: [21] 444https://github.com/rtaiello/pp_dipy/tree/mainC: PPIR based on MI and CC is implemented by extending the Dipy framework of Garyfallidis et al	CBA	BAC	BCA	BAC	Selection 1

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