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**A**: We present them as subroutines here to improve the readability of Algorithm 3. However, we assume Algorithms 4–7 have access to the variables of Algorithm 3 in an implementation and that the Algorithms 4–7 can also use and modify variables of Algorithm 3. The variables of Algorithm 3 modified and used by Algorit... | CBA | CAB | ACB | ABC | Selection 1 |
**A**: We note that the idea of performing global static condensation goes back to the Variational Multiscale Finite Element Method–VMS [MR1660141, MR2300286]. Recently variations of the VMS**B**:
It is essential for the performing method that the static condensation is done efficiently**C**: The solutions of (22) dec... | CAB | ACB | BCA | ABC | Selection 1 |
**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 | CBA | BCA | Selection 3 |
**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**: Actually, we empirically found that roughly 20% of our events (mostly news) contain sub-events. As a rumor is... | ACB | CAB | CAB | CAB | Selection 1 |
**A**: However, if we initialize with η<1/ℒ(𝐰(0))𝜂1ℒ𝐰0\eta<1/\mathcal{L}(\mathbf{w}(0))italic_η < 1 / caligraphic_L ( bold_w ( 0 ) ) then it is straightforward to show the gradient descent iterates maintain bounded local smoothness**B**: Assumption 1 includes many common loss functions, including the logistic, exp... | ACB | CBA | BCA | BAC | Selection 4 |
**A**: It can be seen that although the credibility of some tweets are low (rumor-related), averaging still makes the CreditScore of Munich shooting higher than the average of news events (hence, close to a news). In addition, we show the feature analysis for ContainNews (percentage of URLs containing news websites) fo... | ACB | CAB | ABC | BCA | Selection 2 |
**A**: Language Model-based, how likely aspects are generated by as stastical LM based on the textual representation of the entity 𝖽(e)𝖽𝑒\mathsf{d}(e)sansserif_d ( italic_e )**B**: We model 𝖽(e)𝖽𝑒\mathsf{d}(e)sansserif_d ( italic_e ) as the corresponding Wikipedia article text**C**: We use the unigram model wit... | CBA | BAC | ABC | ACB | Selection 3 |
**A**: The only difference happens to patient 10 and 12 whose intakes are earlier at day.
Further, patient 12 takse approx**B**: 3 times the average insulin dose of others in the morning.**C**: The insulin intakes tend to be more in the evening, when basal insulin is used by most of the patients | BCA | ABC | BAC | CBA | Selection 1 |
**A**: To detect salient items in search array stimuli (see Figure 4d), a mechanism that additionally captures low-level feature contrasts might explain the empirical data better. Besides architectural changes, data augmentation in the context of saliency prediction tasks demonstrated its efficiency to improve the robu... | CBA | CBA | ABC | CAB | Selection 4 |
**A**: This definition leads to the general combinatorial question of whether every word has an optimal marking sequence that is block-extending, or whether the seemingly bad choices of marking a symbol that has only isolated occurrences (and that is not the first symbol) is necessary for optimal marking sequences**B**... | ACB | CAB | BAC | CAB | Selection 3 |
**A**:
A crucial decision in the design of world models is the inclusion of stochasticity**B**: The level of stochasticity is game dependent; however, it can be observed in many Atari games.**C**: Although Atari is known to be a deterministic environment, it is stochastic given only a limited horizon of past observed ... | ABC | ABC | CAB | ACB | Selection 4 |
**A**: 9. The blue line illustrates the total energy consumed (in rolling locomotion mode), while the green line represents the ongoing cumulative energy consumption of the rear legs, indicating it did not exceed the threshold values set by the rear body climbing gait.**B**: This threshold value was established based o... | CBA | CAB | CAB | BCA | Selection 1 |
**A**: Along with its practical significance, research on this problem has lead to technical developments for online algorithms in general.
**B**: We refer the reader to a survey by Coffman et al. [14] and a brief introduction by Johnson [19] for details on bin packing and its applications**C**: Online bin packing find... | CAB | CBA | BAC | BAC | Selection 2 |
**A**: “I was diagnosed with depression”) to obtain self-expressions of depression diagnoses, and then they manually reviewed the matched posts to verify that they were really genuine.
According to the authors, this manual review was strict, expressions like “I have depression”, “I think I have depression”, or “I am de... | ACB | BAC | BCA | CAB | Selection 3 |
**A**: Recently, more and more large-scale deep learning models, such as large language models (Devlin et al., 2019; Brown et al., 2020; Touvron et al., 2023), have been proposed in machine learning**B**: In large-scale model training tasks, the communicated messages become high-dimensional vectors. Due to the latency ... | BCA | CAB | CBA | CAB | Selection 1 |
**A**: Using cross-correlation would produce the same results and would not require flipping the kernels during visualization**B**: operation.**C**:
, where ∗*∗ is the convolution333We use convolution instead of cross-correlation only as a matter of compatibility with previous literature and computational frameworks | BCA | BAC | ABC | ACB | 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 | BCA | Selection 1 |
**A**: , machine components as**B**: Bϕsubscript𝐵italic-ϕB_{\phi}italic_B start_POSTSUBSCRIPT italic_ϕ end_POSTSUBSCRIPT at the magnetic probes rises at compression as crow-barred
shaft current flowing in conductors (i.e.,formulae-sequence𝑖𝑒i.e.,italic_i **C**: italic_e | CAB | ACB | ABC | CBA | Selection 1 |
**A**: The Gridworld problem (Figure 4) is a common RL benchmark**B**: Its relatively small state space permits the Experience Replay (ER) buffer to store all possible state-action pairs**C**: Moreover, this setup allows for the precise computation of the optimal action value function.
| CBA | CAB | ABC | BAC | Selection 3 |
**A**: Other works include GAN-based data augmentation for domain adaptation (Huang et al., 2018; Choi et al., 2019) and panoptic data augmentation (Liu et al., 2019c). However, the majority of GAN based data augmentation has been applied to medical images (Shorten and Khoshgoftaar, 2019). Next, we discuss the GAN base... | ABC | ACB | CBA | CAB | Selection 3 |
**A**: First, we analyze the performance of state-of-the-art methods for mapping random forests into neural networks and neural random forest imitation**B**: That means that the methods aim for the lower-left corner (smaller number of network parameters and higher accuracy). Please note that the y-axis is shown on a lo... | CBA | ABC | ACB | CBA | Selection 3 |
**A**: (2019). It can be shown that the two settings are incomparable in the sense that one does not imply the other (Zhou et al., 2020). Also, our setting is related to the low-Bellman-rank setting studied by Jiang et al. (2017); Dong et al. (2019)**B**:
Broadly speaking, our work is related to a vast body of work on... | BAC | CBA | BCA | CAB | Selection 1 |
**A**: (2015) by a parameter quantization and parameter sharing step, followed by Huffman coding to exploit the non-uniform weight distribution.
This approach yields a reduction in memory footprint by a factor of 35–49 and, consequently, a reduction in energy consumption by a factor of 3–5.**B**: In a follow-up paper, ... | BCA | CAB | CBA | ABC | Selection 2 |
**A**: Finally, recently we became aware of [81, Lemma 5.1], which is similar to Theorem 5**B**: the spaces admit locally finite partition of unity subordinate to the covers), whereas in our version that condition is automatically satisfied since we only consider paracompact spaces. Our proof technique differs from tha... | ACB | BCA | ABC | BAC | Selection 1 |
**A**: Thus, it is hard to see why the normal class is actually separated from the abnormal one. Furthermore, the numerous axis labels introduce even further cluttering and confusion for the users of the standard PCP**B**: Instead, our Adaptive PCP utilizes PCA as a degree-of-interest function and only displays the 8 m... | BAC | BAC | BCA | ACB | Selection 3 |
**A**: This is indeed the search mechanism used in the most representative algorithm of this category, ACO [598], which is inspired by the foraging mechanism of ant colonies. Each ant of the colony describes a trajectory over a graph representation of the search space of the problem at hand, and leaves a trace of phero... | ABC | CAB | CAB | CBA | Selection 4 |
**A**: Three deep clustering methods for general data, DEC [8] DFKM [9], and SpectralNet [7], also serve as an important baseline**B**: All codes are downloaded from the homepages of authors.
**C**: Besides, four GAE-based methods are used, including GAE [20], MGAE [21], GALA [32], and SDCN [31] | CAB | BCA | ACB | ABC | Selection 3 |
**A**: In IPv4 scan to locate the services SMap probes every IP, checking for open ports that correspond to the services that we need; for instance, port 25 for Email, 53 for DNS, 80/443 for Web. To reduce the traffic volume of the scan, instead of probing each IP address for target ports, SMap enables also query of th... | CBA | CAB | CAB | ABC | Selection 1 |
**A**: An alternative approach is to emulate adaptation in natural sensor systems**B**: In this manner, the lifetime of sensor systems can be extended without recalibration.
**C**: The system expects and automatically adapts to sensor drift, and is thus able to maintain its accuracy for a long time | ACB | BCA | CBA | CBA | Selection 1 |
**A**: While these constructions and the involved proofs are generally deemed quite complicated, the situation for semigroups turns out to be much simpler. While it is known that the free semigroup of rank one is not an automaton semigroup [4, Proposition 4.3], the free semigroups of higher rank can be generated by an ... | ACB | BCA | ACB | BAC | Selection 2 |
**A**: To perform the tests, we first randomly sample 5000500050005000 subsets of non-overlapping test instances. We then average the accuracy of each subset across 5555 runs, obtaining 5000500050005000 values**B**: Next, we run the t-tests for HINT and SCR separately on the subset accuracies. As shown in Table 2, the ... | ABC | BCA | CAB | ACB | Selection 1 |
**A**: We focused on privacy policies written in the English language, to enable comparisons with prior corpora of privacy policies**B**: To identify the natural language of each candidate document, we used the open-source Python package Langid (Lui and Baldwin, 2012). Langid is a Naive Bayes-based classifier pretraine... | CBA | BCA | BAC | CBA | Selection 2 |
**A**: EnsembleLens [65] is a VA system that focuses on the identification of the best combination of models by visualizing their correlation**B**: Then, the results are combined and ranked based on the performance outcomes for anomalous cases.
In contrast, our work is not limited to the anomaly detection task, and it ... | BAC | ACB | ABC | ABC | Selection 2 |
**A**: In Weibo, FewRel and Amazon, the settings are 500/1000/1500-shot, 3/4/5-shot and 3/4/5-shot respectively (Table 2).
When the data quantity is small, the advantage of MAML is more significant. In Persona, the C Score and BLEU of MAML outperform baselines on 50-shot and 100-shot settings, but on 120-shot setting, ... | ABC | BAC | BCA | CAB | Selection 3 |
**A**:
Note that there exist some mobile mmWave beam tracking schemes exploiting the position or motion state information (MSI) based on conventional ULA/UPA recently. For example, the beam tracking is achieved by directly predicting the AOD/AOA through the improved Kalman filtering [26], however, the work of [26] onl... | ACB | BAC | BCA | 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 | ABC | CBA | CBA | Selection 2 |
**A**:
In this paper, we study temporal-difference (TD) (Sutton, 1988) and Q-learning (Watkins and Dayan, 1992), two of the most prominent algorithms in deep reinforcement learning, which are further connected to policy gradient (Williams, 1992) through its equivalence to soft Q-learning (O’Donoghue et al., 2016; Schu... | CBA | CAB | ACB | ABC | Selection 3 |
**A**:
To test the effectiveness of depth-wise LSTMs in the multilingual setting, we conducted experiments on the challenging massively many-to-many translation task on the OPUS-100 corpus Tiedemann (2012); Aharoni et al. (2019); Zhang et al**B**: (2020) for fair comparison. We adopted BLEU Papineni et al. (2002) for ... | ACB | CBA | CAB | BCA | Selection 1 |
**A**: sentence φisubscript𝜑𝑖\varphi_{i}italic_φ start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT**B**: Consider the theory
T≜{¬φi∣i∈I}∪{φ}≜𝑇conditional-setsubscript𝜑𝑖𝑖𝐼𝜑T\triangleq\{\neg\varphi_{i}\mid i\in I\}\cup\{\varphi\}italic_T ≜ { ¬ italic_φ start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT ∣ italic_i ∈ ital... | BAC | ACB | ABC | BCA | Selection 3 |
**A**: Qualitative Comparison: To qualitatively show the performance of different learning representations, we visualize the 3D distortion distribution maps (3D DDM) derived from the ground truth and these two schemes in Fig**B**: 8, in which each pixel value of the distortion distribution map represents the distortion... | ABC | BAC | CBA | CBA | Selection 1 |
**A**: 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 the performance on the validation set**B**: The momentum coefficient is set as 0.9 and the weight decay is set as 0.001**C**: We do not adopt any learning rate decay or warm-up strategies.... | ACB | ABC | BAC | BCA | Selection 3 |
**A**: First, we develop algorithms for the simpler polynomial-scenarios model. Second, we sample a small number of scenarios from the black-box oracle and use our polynomial-scenarios algorithms to (approximately) solve the problems on them**B**: Our main goal is to develop algorithms for the black-box setting. As usu... | ABC | BAC | ABC | ABC | Selection 2 |
**A**: Further, the estimations of these rates are substituted into the recursive inequality of the conditional mean square error between the states and the global optimal solution. Finally, by properly choosing the step sizes, we prove that the states of all local optimizers converge to the same global optimal solutio... | ABC | CAB | ACB | CBA | Selection 2 |
**A**: We randomly generate 1,000 queries and calculate the average relative error rate for comparison**B**: In this experiment, we use the approach of aggregate query answering [37] to check the information utility of MuCo**C**: The sequence of the query is expressed in the following form
SELECT SUM(salary) FROM Micro... | ABC | CAB | ABC | BAC | Selection 4 |
**A**: “MP Train” means more points training and “MP Test” means more points testing**B**: “P6 Feature” indicates adding P6 to default P2-P5 levels of FPN for both coarse prediction head and fine-grained point head. “FP16” means mixed precision training.
**C**: Table 2: PointRend’s step-by-step performance on our own v... | ABC | BCA | ABC | ABC | Selection 2 |
**A**: This solves a question raised by Gady Kozma some time ago (see [K], comment from April 2, 2011)**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_POSTSUPERSCR... | BAC | BCA | CAB | ACB | Selection 1 |
**A**: However, when the change of environment is greater, they no longer yield satisfactory performance since their Q𝑄Qitalic_Q function estimate is quite off. This also explains why LSVI-UCB and Epsilon-Greedy outperform ADA-LSVI-UCB at the beginning in the gradually-changing environment, as shown in Figure 1.
**B**... | CAB | BCA | BCA | ACB | Selection 1 |
**A**: The survey contained 19 question items, 2 branching questions, and 3 demographic questions. Respondents were allowed to select multiple options for some question items while the branching questions served to direct them to different sections based on their answer**B**: Although branching means that respondents m... | ACB | BCA | CAB | BAC | Selection 2 |
**A**: Overall, DAN exhibits significantly better performance than GCN, GAT, or their combination. The decentralized attention, which considers neighbors as queries, consistently outperforms the centralized GAT across varying entity degrees.**B**: However, as the degree increases, incorporating DAN yields more performa... | BCA | CAB | ABC | CBA | Selection 4 |
**A**: For each method, the solid line indicates the mean episodic reward of all five seeds, and the shadow area shows the confidence interval (i.e., ±plus-or-minus\pm±Std of episodic rewards among all seeds) of the performance. The result shows that self-supervised exploration enables the agent to obtain higher extrin... | BCA | CAB | CBA | ACB | Selection 3 |
**A**: It is therefore inappropriate for
approximating strongly varying functions, such as the Runge function**B**: Further, we recognize that the Vandermonde approach is inaccurate and even becomes numerically unstable (rising errors) for higher degrees**C**: As expected, (Chebyshev) polynomial interpolation on unifor... | ABC | ACB | BCA | BAC | Selection 4 |
**A**: 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 variables H𝐻Hitalic_H can be partitioned into independent components C𝐶Citalic_C (i.e**B**: the disentangled factor... | ABC | BCA | BCA | BCA | Selection 1 |
**A**: As described above, the output is determined by the 3-pin input, so we will enter 1 with the A2 and A1 connections, the B2 and B1 connections (the reverse is treated as 0), and the corresponding output will be recognized through DFS navigation**B**: In this course, we experiment with a total of eight test cases,... | BCA | ABC | ABC | CBA | Selection 1 |
**A**: Given a finite subset of such permutations, we can compute a group generated by this set**B**: In this paper, we propose a representation of such a group using the concept of linear representation defined through the Koopman operator.**C**:
A finite field, by definition, is a finite set, and the set of all perm... | BCA | BAC | CBA | CBA | Selection 1 |
**A**: In this article we investigated how different view-selecting meta-learners affect the performance of multi-view stacking. In our simulations, the interpolating predictor often performed worse than the other meta-learners on at least one outcome measure**B**: In terms of accuracy it performed very well in the bre... | CBA | ACB | CBA | ABC | Selection 2 |
**A**:
The experimental results (ROC AUC and AP) of the five relevant variable selection techniques are shown in Figure 3. For each technique, its 25 results (each is the average results over the 32 datasets) are presented with a violin plot overlaid by a dot plot**B**: The red dot is the mean value, and the length of... | ACB | BCA | CAB | CBA | Selection 1 |
**A**: Comparison with Faury et al**B**: [2020] Faury et al**C**: [2020] use a bonus term for optimization in each round, and their algorithm performs non-trivial projections on the admissible log-odds. While we do reuse the Bernstein-style concentration inequality as proposed by them, their results do not seem to exte... | CAB | BAC | BAC | ABC | Selection 4 |
**A**: Before delving into the details, in Sec. 3.1 we first introduce our ideas behind these components to deal with the problem of short actions.
**B**: Fig. 2 demonstrates the overall architecture of our proposed Video self-Stitching Graph Network (VSGN)**C**: It is comprised of three components: video self-stitchin... | BAC | CBA | BAC | CAB | Selection 4 |
**A**: Most of the time, less interactive visualizations have been developed for monitoring automatic frameworks [ASY∗19, GSM∗17, KKP∗18, LLN∗18, LTKS19, TBCT∗18]**B**: The use of parallel coordinates plots [ID87] is rather prominent for the visualization of automatic hyperparameter tuners such as HyperOpt [BKE∗15]**C*... | CBA | BAC | CAB | CBA | Selection 2 |
**A**: Additionally, [35] offers an overview of existing swarm robotic applications.
For swarm guidance purposes, certain deterministic algorithms have been developed in [36, 37, 38, 39, 40, 41]**B**: However, these algorithms may become computationally infeasible when dealing with swarms that comprise hundreds to thou... | BCA | ACB | ACB | CBA | Selection 1 |
**A**: As such, matching shape A via shape B to shape C, may lead to a different correspondence than matching shape A directly to C.
**B**: Although this way there is no bias, in general the resulting correspondences are not cycle-consistent**C**: Alternatively, one could solve pairwise shape matching problems between ... | CBA | CAB | CAB | ABC | Selection 1 |
**A**: We presented the first recognition algorithm for both path graphs and directed path graphs**B**: Thus, now these two graph classes can be recognized in the same way both theoretically and algorithmically.
**C**: Both graph classes are characterized very similarly in [18], and we extended the simpler characteriza... | ACB | BCA | BAC | CAB | Selection 1 |
**A**: Mixed-SLIM and Mixed-SCORE perform similarly and both two approaches perform better than OCCAM and GeoNMF under the MMSB setting. Meanwhile, Mixed-SLIM significantly outperforms the other three methods under the DCMM setting.**B**: They suggest that estimating the memberships becomes harder as the purity of mixe... | CAB | CAB | CBA | BCA | Selection 3 |
**A**: (2017); Agarwal et al. (2018); Zhang et al. (2018); Tripuraneni 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 (2019) and the references therein.
Also see recent reviews (Ferreira et al., 2020; Hosseini and Sra, 20... | ABC | BAC | BCA | ACB | Selection 3 |
**A**: However,
as the number of agents increases, joint optimization usually leads to dimensional explosion, which has inhibited the widespread adoption of such methods to a large-scale traffic signal control. To overcome the difficulty, another type of methods are implemented in a decentralized manner. For example, t... | BCA | ABC | ACB | BAC | Selection 4 |
**A**: Recently, and concurrently with the conference version of our work, (?) studied the online knapsack problem under frequency predictions, where each item has a value and a size, and the objective is to maximize the value of items that are accepted (and can fit) in the knapsack. Here, the concept of “frequency pre... | CBA | BAC | BCA | BAC | Selection 1 |
**A**: In this section, we describe the experimental results of the proposed method. First, we evaluate the generative capabilities of the model**B**: Throughout all experiments, we train models with Chamfer distance. We also set λ=0.0001𝜆0.0001\lambda=0.0001italic_λ = 0.0001. We denote LoCondA-HC when HyperCloud is u... | CAB | ACB | BCA | CAB | Selection 2 |
**A**: The previous lemma gives us an understanding of how quickly we can approximate the solution**B**: It remains to understand what the solution even looks like. Considering the global objective function, we have:
**C**: In particular, in coordinates that can be non-zero we are able to have a value that absolutely c... | BCA | ABC | ACB | BCA | Selection 3 |
**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 | CBA | ACB | BAC | BAC | Selection 2 |
**A**: of Patáková [35, Theorem 2.3] into:
**B**: 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 setting, see Section 1.4.1**C**: One immediate application of Theorem 1.2 is the reduction of fra... | CAB | BCA | CBA | CAB | Selection 3 |
**A**: We assume that they know at least the basics regarding the instances and features of their data, but they require further guidance to the feature engineering process**B**: ML experts and practitioners are the main target groups that would benefit the most by using FeatureEnVi**C**: As seen in Section 6, the ML e... | BAC | CAB | CAB | ACB | Selection 1 |
**A**: In MPC, closed-loop performance is pushed to the limits only if the plant under control is accurately modeled, alternatively, the performance degrades due to imposed robustness constraints. Instead of adapting the controller for the worst case scenarios, the prediction model can be selected to provide the best c... | BCA | CBA | CBA | ABC | Selection 1 |
**A**: It is unclear how the explicit bias variables should be defined so that the methods can generalize to all minority groups. GQA-OOD [36] divides the evaluation and test sets into majority (head) and minority (tail) groups based on the answer frequency within each ‘local group’ (e.g., colors of bags), which is a u... | BCA | ABC | BAC | CBA | Selection 3 |
**A**: However, it is still a challenging task due to complex facial appearance.**B**: Different from previous methods, appearance-based methods do not require dedicated devices for detecting geometric features.
They use image features such as image pixel [19] or deep features [17] to regress gaze**C**: Various regress... | CBA | BCA | CAB | BCA | Selection 3 |
**A**: To address this problem, we present in this paper an efficient quantization based pooling method for face recognition using three pre-trained models**B**:
Despite the recent breakthroughs of deep learning architectures in pattern recognition tasks, they need to estimate millions of parameters in the fully conne... | BCA | BAC | CAB | ABC | Selection 2 |
**A**: Such a restricted system may be put in correspondence with a finitary system that detects said loops [SD03, Bro05, Dag21, PP20] where arithmetic assertions can be discharged mechanically [DP20a]**B**: In Example 1 below, we show a hypothetical instance of typechecking.**C**:
We conjecture that finite-time typec... | CBA | BCA | BAC | CBA | Selection 2 |
**A**: The time cost of encrypting a video using the single-value alteration method is depicted in Table V, and it is shown to be acceptably low. Therefore, we suggest that owners select FairCMS-I when the media content size is large and the security requirements is not excessively rigorous. In spite of this, there are... | BCA | CAB | CBA | BAC | Selection 2 |
**A**: FM has been widely used in the field of recommender systems and click-through rate predictions due to its simplicity and effectiveness**B**: However, because FM considers all feature interactions, it has two main drawbacks.**C**:
Factorization machine (FM) Rendle (2010, 2012) are a popular and effective method ... | CAB | BAC | BCA | CAB | Selection 3 |
**A**: [2022] is in essence the Frank-Wolfe algorithm with a modified version of the backtracking line search of Pedregosa et al**B**: We note that the LBTFW-GSC algorithm from Dvurechensky et al**C**: [2020]. In the next section, we provide improved convergence guarantees for various cases of interest for this algorit... | BAC | ABC | CAB | BCA | Selection 1 |
**A**: Note that pausing DFS execution of some search trees increases the time required to explore the entire graph**B**: Nevertheless, we show how to set parameters so that putting on hold DFS over large trees increases the number of passes only by a poly1/εpoly1𝜀\operatorname{poly}1/\varepsilonroman_poly 1 / italic... | BCA | ACB | CBA | BAC | Selection 1 |
**A**: Numerical experiments demonstrate the advantages of B-CPP in saving communication costs.**B**: B-CPP further reduces the communicated data per iteration and is also provably linearly convergent over directed graphs for minimizing strongly convex and smooth objective functions**C**:
We consider an asynchronous b... | BAC | BCA | ACB | CBA | Selection 4 |
**A**:
In this paper, we present a novel formulation for the Personalized Federated Learning Saddle Point Problem (1). This formulation incorporates a penalty term that accounts for the specific structure of the network and is applicable to both centralized and decentralized network settings**B**: These algorithms are... | ACB | ABC | BAC | BCA | Selection 1 |
**A**: Therefore we may also want to evaluate under other distributions such as MW(C)CE, because it constitutes an equilibrium and maximizes value. A final relevant measurement is the number of unique polices found over time. The goal of an MS is to expand policy space (by proposing a joint policy to best respond to). ... | BAC | CAB | BCA | CBA | Selection 4 |
**A**: (2020), but has the advantage of being independent of the range of the queries.
**B**: This lemma resembles Lemma 6 in Jung et al**C**: The simpler part of the argument is posterior accuracy, which we prove can be inherited directly from the sample accuracy of a mechanism | BCA | CBA | BAC | CAB | Selection 2 |
**A**: Hence NP-hard problems do not admit such parameter-decreasing algorithms. To formalize a meaningful line of inquiry, we take our inspiration from the Vertex Cover problem, the fruit fly of parameterized algorithms.
**B**: To illustrate this difficulty, note that strengthening the definition of kernelization to “... | ACB | BAC | CBA | CAB | Selection 3 |
**A**: [160] designed the instance-switching strategy to generate new images through switching different instances of the same class with similar shape and scale.
To better refine the position where the object is pasted, Fang et al**B**: [29] explored appearance consistency heatmap to guide the object placement, based ... | ACB | ABC | BCA | CBA | Selection 3 |
**A**: Our findings reveal that when only 3-day training data are available, non-deep learning models such as LR achieve similar performances as compared to using full data, whereas LSTM models suffer from an increased error rate of 50%, as observed in the case of Chengdu**B**:
Degradation under data scarcity**C**: Th... | BCA | BAC | BCA | ABC | Selection 2 |
**A**: Gal and Ghahramani showed that dropout networks can be obtained as a variational approximation to deep Gaussian processes gal2016dropout . Therefore, it can be expected that, at least when normality assumptions are satisfied, this method can outperform more ad hoc approaches.**B**:
Dropout layers were initially... | BAC | BAC | CAB | ABC | Selection 3 |
**A**:
Dynamics is an important element in music, as they are often used by musicians to add excitement and emotion to songs. Given that the tokens we choose do not contain performance information, it is interesting to see how a machine model would “perform” a piece by deciding these volume changes, a task that is ess... | ABC | ABC | BCA | ACB | Selection 4 |
**A**: [10] for a survey), where the colors of any two adjacent vertices have to differ by at least k𝑘kitalic_k and the colors of any two vertices within distance 2222 have to be distinct.
**B**: This description draws a comparison e.g**C**: to L(k,1)𝐿𝑘1L(k,1)italic_L ( italic_k , 1 )-labeling problem (see e.g | BAC | CAB | ACB | BCA | Selection 2 |
**A**:
A. Graves, S. Fernández, F. Gomez, and J. Schmidhuber, “Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks,” in Proc. 23rd Int**B**: Learning (ICML), Pittsburgh, USA, Jun. 2006, pp. 369–376.**C**: Conf. Mach | ACB | ABC | BCA | BCA | Selection 1 |
**A**: In inference, we can simply discard the two modules and use the basic segmentation network as a normal point cloud segmentation network to get the segmentation predictions**B**: Therefore, no extra memory and computational resources are introduced at test time.
**C**: The two modules implicitly guide the optimiz... | BAC | CBA | BCA | ABC | Selection 3 |
**A**: As we can observe,
ours (full model) achieves a large gain (2.68% on the moderate) over 3D-CAT, meaning that directly using the network predictions are not effective enough for learning the geometric representations, thus verifying the importance of the proposed geometric formula**B**: By comparing Geo-SV2, Geo-... | BAC | ABC | BAC | ACB | Selection 2 |
**A**:
Figure 5: The results of weakly supervised annotation (1st row) and the ground truth (2nd row)**B**: The GCN now has the ability to classify the type of segments, which will benefit the following FPNS step. In these figures, Non-Text Segments are not displayed for clarity.**C**: The Interval Segments and Char S... | BCA | BCA | CAB | ACB | Selection 4 |
**A**: We briefly describe some of the original sorting techniques as well as various parallel sorting algorithms in Section 2**B**: In Section 3, we introduce the proposed method. The experimental results are presented in Section 4. Finally, we draw the conclusions of the study in Section 5.
**C**: The remainder of th... | ACB | BAC | BCA | BAC | Selection 3 |
**A**: We study both block-triangular and block-diagonal preconditioners for the system matrix (1)**B**: We consider the following preconditioner:
**C**: For block-triangular preconditioners, we focus on a lower triangular type with left preconditioning because an upper triangular one with right preconditioning can be ... | BAC | ACB | CBA | BAC | Selection 2 |
**A**: For CIFAR-10 we search for a learning rate in the range [0.0001, 0.00001], for MIMIC-III we search in the range [0.1, 0.001], and for ModelNet40 we search in the range [0.001, 0.00005]**B**: For each Q𝑄Qitalic_Q and K𝐾Kitalic_K, we let TDCD train for 5,000 iterations for CIFAR-10, 10,000 iterations for MIMIC-I... | BAC | CBA | BCA | BAC | Selection 3 |
**A**: Let ℬℬ\mathcal{B}caligraphic_B be another tensor with the same size as 𝒜𝒜\mathcal{A}caligraphic_A**B**: Under the same conditions as defined in Definition 7, if the following equation holds:
**C**: We can further extend the concept of T-eigenvalues into generalized T-eigenvalues, similar to the case of general... | CBA | BCA | ABC | ABC | Selection 2 |
**A**:
Objective evaluation**B**: 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%**C**: Table 1 shows the results achieved on the Places2 dataset, ... | ACB | CAB | ABC | BAC | Selection 3 |
**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... | BCA | CBA | CBA | BAC | Selection 4 |
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