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**A**: We note that after applying the function SlotUsagePattern, the resulting SLP only required 12121212 memory slots and could be evaluated in the same time as our MSLP**B**: When faced with an SLP not designed to be memory efficient, one might not expect such drastic improvements.
**C**: This is due to the fact tha... | ACB | BAC | CAB | ABC | Selection 1 |
**A**: From now on, we concentrate on approximating P𝑃Pitalic_P so that (25) can be accurately and efficiently solved.
**B**: 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**C**: Solving (25) on the other hand invol... | CAB | BAC | ABC | BCA | Selection 1 |
**A**: Moreover, Alg-A is more stable than the alternatives.
During the iterations of Alg-CM, the coordinates of three corners and two midpoints of a P-stable triangle (see Figure 37) are maintained**B**: Alg-CM uses an involved subroutine (far more complicated than ours given in Algorithm 1) to update the coordinates ... | ABC | BCA | ACB | CAB | Selection 3 |
**A**: Actually, we empirically found that roughly 20% of our events (mostly news) contain sub-events. As a rumor is often of a long circulating story [10], this results in a rather long time span. In this work, we develop an event identification strategy that focuses on the first 48 hours after the rumor is peaked. We... | BAC | ACB | CAB | CBA | Selection 3 |
**A**: 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 parameterization asymptotically to the maximum margin solution with unit nuclear norm**B**: The follow-up paper (Gunasekar... | BAC | BCA | ACB | BCA | Selection 1 |
**A**: The best one is NumOfChar which is the average number of different characters in tweets. PolarityScores is the best feature when we tested the single tweets model, but its performance in time series model is not ideal**B**: It is true that rumor contains more negative sentiment, but in an event (rumor or news) p... | BCA | BAC | ABC | CBA | Selection 1 |
**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... | CBA | CAB | CBA | ACB | Selection 2 |
**A**: Only one of the patients suffers from diabetes type 2 and all are in ICT therapy. In terms of time since being diagnosed with diabetes, patients vary from inexperienced (2 years) to very experienced (35 years), with a mean value of 13.9 years.**B**:
Table 1 shows basic patient information. Half of the patients ... | BCA | BCA | BAC | CAB | Selection 4 |
**A**: The minimal GPU memory utilization was measured with TensorFlow in megabytes (MB) and included the requirements for initializing a testing session. Finally, we estimated the floating point operations per second (FLOPS) at a scale of 9 orders of magnitude.
**B**: After running each network on 10,000 test set inst... | CBA | CAB | ACB | BCA | Selection 1 |
**A**: Before presenting the main results of this section, let us briefly discuss some inapproximability results for MinLoc that directly follow from the reductions of Section 4 and known results about cutwidth approximation**B**: Firstly, it is known that, assuming the Small Set Expansion Conjecture (denoted SSE; see ... | ABC | CAB | CAB | BCA | Selection 1 |
**A**: in fewer step than 100k) with more directed exploration policies. In Figure 9 in the Appendix we present the cumulative distribution plot for the (first) point during learning when the maximum score for the run was achieved in the main training loop of Algorithm 1.
**B**: In some games, good policies could be le... | BAC | CBA | BCA | BCA | Selection 2 |
**A**:
Several avenues for future exploration are suggested based on the constraints of the work discussed in this paper**B**: Furthermore, despite the common usage of climbing gaits for step negotiation in wheel/track-legged robots, it is crucial to validate the energy efficiency of the suggested climbing gaits. Futu... | CBA | BCA | ACB | CBA | Selection 3 |
**A**: The smaller the value of α𝛼\alphaitalic_α is, the more conservative the algorithm is. Our analysis is based on two possibilities in the final packing of the algorithm. In the first case (case I), all critical bins receive a critical item, while in the second case (case II) some of them have their reserved space... | CAB | CAB | CBA | ACB | Selection 3 |
**A**: Finally, Section 6 summarizes the main conclusions derived from this study and suggests possible future work.
**B**: Section 5 goes into details of the main contributions of our approach by analyzing quantitative and qualitative aspects of the proposed framework**C**: In Section 4 the proposed framework is compa... | CAB | BCA | CBA | BCA | Selection 3 |
**A**: Xu and Huang (2022) propose DEF-A to solve the convergence problem by using detached error feedback (DEF) technique 111Xu and Huang (2022) proposes two algorithms: DEF and DEF-A**B**: Since DEF-A enhances the generalization performance of DEF, we only consider DEF-A in this paper..
The momentum variant of DEF-A ... | BCA | BAC | ABC | ABC | Selection 1 |
**A**:
, where ∗*∗ is the convolution333We use convolution instead of cross-correlation only as a matter of compatibility with previous literature and computational frameworks**B**: operation.**C**: Using cross-correlation would produce the same results and would not require flipping the kernels during visualization | ABC | CBA | BCA | ACB | Selection 4 |
**A**: And then UAV compares two payoffs. If the payoff of new strategy is larger, the current strategy will be replaced by the new strategy; if the current payoff strategy is large, it will remain in the current strategy. However, under highly dynamic scenarios, complicate network conditions make UAVs hard to calculat... | CAB | BCA | CBA | ABC | Selection 2 |
**A**: italic_e **B**: , ψ|Γ=Cevaluated-at𝜓Γ𝐶\psi|_{\Gamma}=Citalic_ψ | start_POSTSUBSCRIPT roman_Γ end_POSTSUBSCRIPT = italic_C (constant)), corresponding to having**C**: the boundary condition (∇∥ψ)|Γ=0evaluated-atsubscript∇parallel-to𝜓Γ0\left(\nabla_{\parallel}\psi\right)|_{\Gamma}=0( ∇ start_POSTSUBSCRIPT ∥ end_... | BAC | BAC | ABC | BCA | Selection 4 |
**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 | ABC | ABC | BAC | Selection 4 |
**A**: (2018) proposed a pyramid attention based network, for semantic segmentation**B**: They combined an attention mechanism and a spatial pyramid to extract precise dense features for pixel labeling instead of complicated dilated convolution and artificially designed decoder networks. Chen et al. (2016) applied atte... | ABC | ABC | BAC | BCA | Selection 4 |
**A**: 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 logarithmic scale.**B**: The results are shown in Figure 4 for different numbers of training examples per class.
For each method, the average number of p... | ACB | CBA | BAC | ACB | Selection 2 |
**A**: To answer this question, we propose the first policy optimization algorithm that incorporates exploration in a principled manner. In detail, we develop an Optimistic variant of the PPO algorithm, namely OPPO**B**: As is shown subsequently, solving such a subproblem corresponds to one iteration of infinite-dimens... | CAB | ACB | BCA | CBA | Selection 2 |
**A**: (2016) proposed deep compression, which extends the work Han et al**B**: (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 reducti... | BCA | CBA | BAC | ACB | Selection 1 |
**A**: We also thank Prof. Mikhail Katz and Prof. Michael Lesnick for explaining to us some aspects of their work**B**: We thank Dr. Qingsong Wang for bringing to our attention the paper [76] which was critical for the proof of Theorem 1. Finally, we thank Dr. Alexey Balitsky for pointing out an imprecision in the stat... | CBA | ABC | ACB | BCA | Selection 4 |
**A**: On the one hand, we found the bar chart (a) to be better when comparing the projection’s average with the selection’s average when we search for discrete k-values, and during the initial state (no selection of points), where the user can easily distinguish the bars having the same size.
It can optionally be repl... | CBA | BCA | BAC | BCA | Selection 1 |
**A**: In addition, comparisons have been often inadequate, leading to problems of reproducibility and applicability. This problem has captured the interest of other researchers, leading to several papers on various aspects related to bad comparisons and the increasing number of unoriginal proposals, even to the point ... | CBA | ACB | BCA | CBA | Selection 3 |
**A**: The adaptive learning will induce the model to exploit the high-level information. In particular, AdaGAE is stable on all datasets.
**B**: Although GAE-based models (GAE, MGAE, and GALA) achieve impressive results on graph type datasets, they fail on the general datasets, which is probably caused by the fact tha... | BAC | ACB | CBA | CAB | Selection 3 |
**A**: Previous studies infer spoofability based on measurements of a limited set of networks, e.g., those that operate servers with faulty network stack (Kührer et al., 2014) or networks with volunteers that execute the measurement software (Beverly and Bauer, 2005; Beverly et al., 2009; Mauch, 2013; Beverly et al., 2... | CBA | ACB | ACB | BCA | Selection 4 |
**A**: When something changes, the entire system is taken offline and modified to fit the new situation**B**: This process is costly and disruptive; adaptation similar to that in nature might make such systems more reliable and long-term, and thus cheaper to operate.
**C**: It is common to try to avoid such changes in ... | ABC | CBA | CBA | BCA | Selection 4 |
**A**: However, there do not seem to be constructions for presenting arbitrary free products of self-similar groups in a self-similar way**B**: In fact, the free product of two automaton semigroups S𝑆Sitalic_S and T𝑇Titalic_T is always at least
very close to being an automaton semigroup: adjoining an identity to S⋆T⋆... | CAB | ABC | ACB | ABC | Selection 3 |
**A**: Since Wu and Mooney (2019) reported that human-based textual explanations Huk Park et al. (2018) gave better results than human-based attention maps for SCR, we train all of the SCR variants on the subset containing textual explanation-based cues**B**: SCR is trained in two phases. For the first phase, which str... | ABC | BCA | CBA | BCA | Selection 1 |
**A**: While both the researchers had substantial prior experience with privacy policies, the privacy expert was consulted to eliminate uncertainty in the annotations of a few documents. Lack of agreement in the annotations occurred for six documents, which were settled by discussion with the expert.
Out of 1,600 docum... | CAB | ACB | BAC | BAC | Selection 1 |
**A**: Another positive opinion from E3 was that, with a few adaptations to the performance metrics, StackGenVis could work with regression or even ranking problems.
E3 also mentioned that supporting feature generation in the feature selection phase might be helpful**B**: To avoid an asymmetric design and retain a lowe... | BAC | CBA | CBA | ACB | Selection 4 |
**A**: In Persona and Weibo, the performance of MAML is similar to that of Transformer-F, while MAML performs significantly better than Transformer-F when tasks are different. A possible explanation is that if there is no clear distinction between tasks, the meta-learning setting can be viewed as a transfer learning se... | CAB | ABC | ACB | ACB | Selection 1 |
**A**: Then the system setup of the considered UAV mmWave network is described in Section II-B. Finally, the beam tracking problem for the CA-enabled UAV mmWave network is modeled in Section II-C.**B**:
A CCA-enabled UAV mmWave network is considered in this paper**C**: Here, we first establish the DRE-covered CCA mode... | BAC | CAB | BCA | BCA | Selection 2 |
**A**: This will be bootstrapped to the multi-color case in later sections**B**: We**C**: 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... | ACB | ABC | BAC | CBA | Selection 1 |
**A**: (2019); Chen et al. (2019b) study the convergence of Q-learning. When the value function approximator is nonlinear, TD possibly diverges (Baird, 1995; Boyan and Moore, 1995; Tsitsiklis and Van Roy, 1997). Bhatnagar et al. (2009) propose nonlinear gradient TD, which converges but only to a locally optimal solutio... | CBA | CAB | CBA | BCA | Selection 4 |
**A**:
Table 3 shows that a 2-layer feed-forward neural network (Equation 6) in the depth-wise LSTM outperforms the original computation of the LSTM hidden state which uses only one layer (Equation 5), which is consistent with intuition**B**: However, even with only one layer for the hidden state computation and with ... | ABC | CBA | CBA | ACB | Selection 1 |
**A**: However, notice that the T0subscript𝑇0T_{0}italic_T start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT quotient of
Struct(σ)Structσ\operatorname{Struct}(\upsigma)roman_Struct ( roman_σ ) is sober when τ=τ⊆iτsubscriptτsubscript𝑖\uptau=\uptau_{\subseteq_{i}}roman_τ = roman_τ start_POSTSUBSCRIPT ⊆ start_POSTSUBSCRIPT itali... | BCA | ABC | ABC | ABC | Selection 1 |
**A**: Next, we introduce the network architecture and training loss in Section III-B. Finally, Section III-C describes the transformation between the ordinal distortion and distortion parameter.**B**:
In this section, we describe how to learn the ordinal distortion given a single distorted image**C**: We first define... | BAC | CAB | BCA | BAC | Selection 2 |
**A**:
To further verify the superiority of SNGM with respect to LARS, we also evaluate them on a larger dataset ImageNet [2] and a larger model ResNet50 [10]**B**: As recommended in [32], we use warm-up and polynomial learning rate strategy.**C**: We train the model with 90 epochs | ABC | CBA | ACB | ABC | Selection 3 |
**A**: The most general way to represent the scenario distribution 𝒟𝒟\mathcal{D}caligraphic_D is the black-box model [24, 12, 22, 19, 25], where we have access to an oracle to sample scenarios A𝐴Aitalic_A according to 𝒟𝒟\mathcal{D}caligraphic_D**B**: We also consider the polynomial-scenarios model [23, 15, 21, 10]... | ABC | CAB | ACB | CBA | Selection 1 |
**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])... | BCA | ACB | ACB | ABC | Selection 1 |
**A**: We randomly generate 1,000 queries and calculate the average relative error rate for comparison**B**: The sequence of the query is expressed in the following form
SELECT SUM(salary) FROM Microdata**C**: In this experiment, we use the approach of aggregate query answering [37] to check the information utility of ... | BAC | ABC | CAB | BCA | Selection 4 |
**A**: It produces smooth object boundaries with much finer details than previously two-stage detectors like MaskRCNN, which naturally benefits large object instances and complex scenes**B**: PointRend performs point-based segmentation at adaptively selected locations and generates high-quality instance mask**C**: Furt... | CBA | ABC | BAC | ACB | Selection 3 |
**A**:
In version 1 of this note, which can still be found on the ArXiv, we showed that the analogous version of the conjecture for complex functions on {−1,1}nsuperscript11𝑛\{-1,1\}^{n}{ - 1 , 1 } start_POSTSUPERSCRIPT italic_n end_POSTSUPERSCRIPT which have modulus 1111 fails**B**: This solves a question raised by ... | CBA | CBA | ABC | CAB | Selection 3 |
**A**: Our algorithm is summarized in Algorithm 1**B**:
Our proposed algorithm LSVI-UCB-Restart has two key ingredients: least-squares value iteration with upper confidence bound to properly handle the exploration-exploitation trade-off (Jin et al., 2020), and restart strategy to adapt to the unknown nonstationarity**... | CAB | BCA | BAC | ACB | Selection 3 |
**A**: They actively verify news before sharing by checking with multiple sources found through the search engine and with authoritative information found in government communication platforms, and post corrections and warnings when they encounter fake news**B**:
In general, respondents possess a competent level of di... | CBA | ABC | BCA | BAC | Selection 4 |
**A**:
The results on the ZH-EN dataset are depicted in Figure 7. For entities with only a few neighbors, the advantage of leveraging DAN is not significant**B**: Overall, DAN exhibits significantly better performance than GCN, GAT, or their combination. The decentralized attention, which considers neighbors as querie... | ACB | BAC | ABC | CBA | Selection 1 |
**A**: In section III-B, we present the detail of the optimizing process. In section III-C, we analyze the result of VDM used in ‘Noisy-Mnist’ that models the multimodality and stochasticity in MDP. In section III-D, we present the method for calculating a tighter upper bound of the negative log-likelihood of transitio... | BCA | CBA | ACB | CAB | Selection 4 |
**A**: In doing so, we revisit earlier results by Carl de Boor and Amon Ros [28, 29] and answer their question from our perspective.**B**: That is: For given arbitrary nodes P𝑃Pitalic_P, determine the polynomial space ΠΠ\Piroman_Π such that
P𝑃Pitalic_P is unisolvent with respect to ΠΠ\Piroman_Π**C**: We complement th... | BCA | ABC | ACB | CBA | Selection 4 |
**A**: The key observation that we make is that the DR learning problem can be cast as a style transfer task [DBLP:conf/cvpr/GatysEB16], thus allowing us to borrow techniques from this extensively explored area.
**B**: The framework is general and can utilize any DGM**C**: Furthermore, even though it involves two stage... | CAB | BAC | ACB | ACB | Selection 1 |
**A**: Graphs are expressed in red and blue numbers in cases where there is no direction of the main line (the main line that can be passed in both directions) and the direction of the main line (the main line that can only be moved outward from the middle of the set of vertex).
**B**: Graph described in Fig**C**: 4 i... | BCA | BAC | ABC | CAB | Selection 4 |
**A**: In this paper, we propose a representation of such a group using the concept of linear representation defined through the Koopman operator.**B**:
A finite field, by definition, is a finite set, and the set of all permutation polynomials over the finite field forms a group under composition**C**: Given a finite ... | ABC | BCA | CAB | BAC | Selection 3 |
**A**: In terms of raw test accuracy the nonnegative lasso is the best performing meta-learner, followed by the nonnegative elastic net and the nonnegative adaptive lasso**B**: The results of applying MVS with the seven different meta-learners to the colitis data can be observed in Table 2**C**: In terms of AUC and H, ... | BCA | CBA | BAC | BCA | Selection 3 |
**A**:
It is worth noting that the key difference between the two DepAD methods (FBED-CART-PS and FBED-CAR-Sum) and ALSO lies in their relevant variable selection phase**B**: The two DepAD methods learn and use the MB of a variable as its relevant variables, while ALSO, for each variable, uses all other variables as t... | CBA | ABC | BAC | CAB | Selection 2 |
**A**: [2010] but has a multiplicative κ𝜅\kappaitalic_κ factor in the bound.**B**:
Comparison with Oh & Iyengar [2019] The Thompson Sampling based approach is inherently different from our Optimism in the face of uncertainty (OFU) style Algorithm CB-MNL**C**: However, the main result in Oh & Iyengar [2019] also relie... | CAB | ACB | ACB | ACB | Selection 1 |
**A**: Methods using this strategy are efficient owing to the small input scale, but would harm short actions especially those in long videos, since these short actions are essentially down-scaled and their information easily gets lost or distorted. However, it is non-trivial to up-scale videos as input instead for the... | BAC | CAB | BAC | ACB | Selection 2 |
**A**: Evaluation with the Test and External Validation Sets**B**: For the test data set, the reported accuracy was approximately 87%.
In our case, we reached 89% for accuracy with the final voting ensemble (macro-average).**C**: To verify whether our findings were reliable, we applied the resulting majority-voting ens... | ACB | CAB | CAB | BAC | Selection 1 |
**A**: In addition, an equivalence is proven between the feasibility of the MINLP and the feasibility of a mixed-integer linear program (MILP) for a particular case where the agents move along the nodes of a complete graph. While this study assumes homogeneous swarms for Markov chain synthesis subject to finite-horizon... | BAC | BAC | CAB | ACB | Selection 3 |
**A**: In contrast, HiPPI and our method require shape-to-universe representations. To obtain these, we use synchronisation to extract the shape-to-universe representation from the pairwise transformations**B**: Throughout this section we also report results of the initialisation methods ZoomOut and ZoomOut+Sync. Furth... | CBA | BCA | ACB | BAC | Selection 3 |
**A**: In this section we analyze all steps of algorithm RecognizePG**B**: We want to explain them in details and compute the computational complexity of the algorithm**C**: Some of these steps are already discussed in [22], anyway, we describe them in order to have a complete treatment.
| ACB | ABC | CAB | CBA | Selection 2 |
**A**:
Panels (e) and (f) of Figure 1 report the numerical results of these two sub-experiments**B**: 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 ... | BCA | ACB | CBA | CBA | Selection 2 |
**A**: See, e.g., Welling and Teh (2011); Chen et al. (2014); Ma et al. (2015); Chen et al. (2015); Dubey et al. (2016); Vollmer et al**B**: (2018); Cheng and Bartlett (2018); Chatterji et al. (2018); Wibisono (2018); Bernton (2018); Dalalyan and Karagulyan (2019); Baker et al. (2019); Ma et al. (2019a, b); Mou et al. ... | BCA | BAC | ABC | ACB | Selection 4 |
**A**: We conduct extensive experiments and demonstrate the superior performance of our method over the state-of-the-art. We have collected and released more complex scenarios containing different structures 777https://github.com/zhuliwen/RoadnetSZ, and will improve the method based on these scenarios in the future. In... | CBA | BCA | BCA | ABC | Selection 1 |
**A**: To this end, we will relate the cost of the packing of ProfilePacking to the packing that the algorithm would output if the prediction were error-free, which will allow us to apply the result of Lemma 2**B**: Specifically, we will argue that in the presence of prediction error, the cost of ProfilePacking may be ... | ABC | BCA | ACB | ACB | Selection 2 |
**A**: To that end, we propose a novel framework, LoCondA, capable of generating and reconstructing high-quality 3D meshes**B**: This framework extends the existing base hypermodels (Spurek et al., 2020a, b) with an additional module designed for mesh generation that relies on a parametrization of local surfaces, as sh... | ABC | BCA | BAC | ACB | Selection 1 |
**A**: Their method covers the Euclidean case and the algorithm has O(1/N)𝑂1𝑁O(1/N)italic_O ( 1 / italic_N ) convergence rate.
Our paper proposes an algorithm based on adding Lagrangian multipliers to consensus constraints, which is analogical to [61], but our method works in a general proximal smooth setup and achi... | ACB | BCA | BCA | BAC | Selection 4 |
**A**: We proceed by trying to find a counterexample based on our previous observations**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**: In this section we present ... | CAB | BAC | BCA | ACB | Selection 3 |
**A**: This technique, which we briefly outline here, was specifically designed for complete intersection patterns**B**: A major part of this paper, all of Sections 3 and 4, is devoted to adapt it to handle the k𝑘kitalic_k-partite structure of colorful intersection patterns.**C**:
The proof of Theorem 2.1 is quite in... | ABC | ABC | BCA | ACB | Selection 3 |
**A**: the current result according to three validation metrics in Fig. 1(e).**B**: Fig. 1(d)); and
(v) contrast the performances of the best predictive performance found so far vs**C**: (iv) during the detailed examination phase, check the different transformations of the features with statistical measures and compare... | BCA | ACB | CBA | BAC | Selection 3 |
**A**: After the initial learning phase the algorithm quickly finds the region where the simulation is feasible with respect to the constraints. The confidence interval in the cost prediction narrows for the infinity shaped trajectory, which is likely due to a more clear minimum in the cost of this geometry. The optimi... | CAB | ACB | BAC | BAC | Selection 1 |
**A**: While the community has largely focused on training procedures for bias mitigation, an exciting avenue for future work is to incorporate appropriate inductive biases into the architectures, perhaps endowing them with the ability to choose the the minimal computational power to do a task so that they are less sen... | BAC | BCA | CAB | ACB | Selection 2 |
**A**: Two eye asymmetry Property.
Cheng et al. discover the ’two eye asymmetry’ property that the appearances of two eyes are different while the gaze directions of two eyes are approximately the same [44]**B**: They design an asymmetry regression network for adaptively weighting two eyes.**C**: Based on this observat... | ACB | BAC | ABC | BCA | Selection 1 |
**A**:
Another efficient face recognition method using the same pre-trained models (AlexNet and ResNet-50) is proposed in almabdy2019deep and achieved a high recognition rate on various datasets**B**: It consists of applying a TL technique to fine-tune the pre-trained models to the problem of masked face recognition ... | ABC | ACB | BCA | ABC | Selection 2 |
**A**: Relatedly, refer to Das and Pfenning [DP20a] for a proof of type safety for a session type system with arithmetic refinements**B**: In contrast to the termination proof for base SAX [DPP20], we explicitly construct a model of SAX in sets of terminating configurations, also known as semantic typing [App01, HLKB21... | CAB | ABC | BCA | ABC | Selection 3 |
**A**:
Figure 13: The comparison of cloud-side computational efficiency between FairCMS-I and FairCMS-II**B**: The bars and polyline correspond to the left and right Y-axes, respectively**C**: The time consumed by FairCMS-II is 100 times the reading on the Y-axis. (a) Efficiency comparison under different number of us... | CAB | ABC | ACB | BCA | Selection 2 |
**A**: This makes HOFM difficult to use in practice. To address the limitations of FM in capturing higher-order feature interactions, several variants have been proposed that utilize deep neural networks (DNNs) Zhang et al**B**: (2016); He and Chua (2017); Cheng et al. (2016); Guo et al. (2017).
Factorisation-machine s... | BAC | ABC | BCA | CAB | Selection 3 |
**A**: We denote line search by LS, zeroth-order oracle by ZOO, second-order oracle by SOO, domain oracle by DO, local linear optimization oracle by LLOO, and the assumption that 𝒳𝒳\mathcal{X}caligraphic_X is polyhedral by P(𝒳)𝑃𝒳P(\mathcal{X})italic_P ( caligraphic_X )**B**: Table 1:
Number of iterations needed ... | ABC | CBA | BAC | ABC | Selection 3 |
**A**: The rest of our algorithm is divided into multiples phases. In each phase, we iteratively improve the approximation ratio of our current matching M𝑀Mitalic_M by finding a set of disjoint M𝑀Mitalic_M-augmenting paths (and performing the augmentations accordingly). We stop the algorithm after certain number of p... | BCA | ACB | CAB | BAC | Selection 3 |
**A**: Thus, B-CPP is more flexible, and due to its broadcast nature, it can further save communication over CPP in certain scenarios [63]**B**: We show that B-CPP also achieves linear convergence for minimizing strongly convex and smooth objectives.
**C**: In the second part of this paper, we propose a broadcast-like ... | CBA | ABC | CAB | BCA | Selection 4 |
**A**: This extends the classical PFL problem to a broader class of problems beyond the classical minimization problem**B**: It furthermore covers various communication topologies and hence goes beyond the centralized setting.
**C**: We present a new SPP formulation of the PFL problem (1) as the decentralized min-max m... | BAC | ABC | BCA | ABC | Selection 3 |
**A**: In this work we propose using correlated equilibrium (CE) (Aumann, 1974) and coarse correlated equilibrium (CCE) as a suitable target equilibrium space for n-player, general-sum games333We mean games (also called environments) in a very general sense: extensive form games, multi-agent MDPs and POMDPs (stochastic... | ACB | BCA | CAB | ABC | Selection 1 |
**A**: It might also be possible to relax our assumption that data elements are drawn iid to a weaker independence requirement. Furthermore, it would be interesting to explore an extension from linear queries to general low-sensitivity queries.
**B**: One small extension of the present work would be to consider queries... | CBA | CBA | CBA | CAB | Selection 4 |
**A**: A substantial theoretical framework has been built around the definition of kernelization [17, 22, 27, 29, 31]**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 complexity-the... | BCA | BAC | CBA | ABC | Selection 4 |
**A**: [182] proposed to train a classifier to predict the zone (e.g., low, middle, high) of the histogram which can be best matched between foreground and background, and then adjust the foreground color to match the selected zone between foreground and background. [143] explored decomposing an image into a multi-reso... | BAC | CAB | ABC | ACB | Selection 2 |
**A**:
Impact of Context Data**B**: By leveraging POI data for region matching, our proposed RegionTrans method achieves lower error rates than fine-tuning in most cases**C**: This finding, coupled with the results presented in Section III-A, underscores the importance of multi-modal data in CityNet and verifies the c... | ABC | CBA | BAC | CAB | Selection 1 |
**A**: In the context of classification problems, where especially the former issue plays a role guo2017calibration , a wide variety of calibration methods is available: Platt scaling, temperature scaling, isotonic regression, etc. In general these methods take the output distribution of the trained predictor and modif... | ABC | CBA | BAC | ACB | Selection 1 |
**A**: We can also modify the output layer of the Transformer so that it predicts multiple tokens at once with different heads.**B**: 1(b)**C**: Instead of feeding the token embedding of each of them individually to the Transformer, we can combine the token embedding of either the four tokens for MIDI scores or six tok... | ABC | CBA | BAC | BAC | Selection 2 |
**A**: This description draws a comparison e.g**B**: [10] for a survey), where the colors of any two adjacent vertices have to differ by at least k𝑘kitalic_k and the colors of any two vertices within distance 2222 have to be distinct.
**C**: to L(k,1)𝐿𝑘1L(k,1)italic_L ( italic_k , 1 )-labeling problem (see e.g | BCA | CAB | ACB | ABC | Selection 3 |
**A**:
Recently, there are also investigations on semantic communications for other transmission contents, such as image and speech. A DL-enabled semantic communication system for image transmission, named JSCC, has been developed in[14]**B**: Particularly, a joint image transmission-recognition system has been develo... | ABC | ACB | ABC | CBA | Selection 2 |
**A**: Figure4(a) shows the affinity learned in CSFR between the input pairs**B**: Figure4(b) shows the affinity learned in ISFR in each sample**C**: We show the affinity map on the left to the selected point on the right. The point clouds are sparse since we perform CSFR and ISFR in down-sampled features. Obviously, b... | ABC | CAB | ACB | BAC | Selection 1 |
**A**: In contrast to these methods, we only use the monocular image as input without any extra burden.**B**: Existing works [6, 28, 26, 25, 5, 10] have considered using external pretrained networks, extra training data, and prior knowledge to improve the performance of monocular 3D object detection.
Particularly, Deep... | ACB | CBA | BCA | ACB | Selection 2 |
**A**: 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.**B**: The Interval Segments and Char Segments are shown with different colors**C**:
Figure 5: The results of weakly supervised annotation (... | ACB | ACB | CBA | ABC | Selection 3 |
**A**: The Compute Unified Device Architecture (CUDA) is a parallel computing platform for general computing on GPUs. Most parallel sorting algorithms are variants of standard, well-known sorting algorithms adapted to GPU hardware architecture**B**: For example, Cederman designed a quick sort for the GPU platform Ceder... | ACB | CAB | BCA | BAC | Selection 3 |
**A**: The authors would like to thank Mingjian Ding, and Baoxuan Zhu for providing an alternative proof of the Hurwitz stability of polynomials (25). They also thank Jarle Sogn for communicating on Schur complement based preconditioners.
The work of M. Cai is partially supported by the NIH-RCMI grant through 347 U54MD... | ACB | CAB | ABC | CAB | Selection 3 |
**A**: The authors in works (Chen et al., 2020; Hardy et al., 2017; Yang et al., 2019b; Wu et al., 2020; Feng and Yu, 2020; Kang et al., 2020) propose vertical federated learning algorithms for single-tier communication networks, but they do not use local iterations in the parties during training**B**: Several works ha... | BAC | CBA | BCA | ACB | Selection 1 |
**A**: We can further extend the concept of T-eigenvalues into generalized T-eigenvalues, similar to the case of generalized matrix eigenvalues**B**: Let ℬℬ\mathcal{B}caligraphic_B be another tensor with the same size as 𝒜𝒜\mathcal{A}caligraphic_A**C**: Under the same conditions as defined in Definition 7, if the fol... | BCA | CBA | ABC | CBA | Selection 3 |
**A**: Furthermore, a Bi-directional Gated Feature Fusion module is introduced followed by a Contextual Feature Aggregation module to refine the results, with both semantically reasonable structures and detail-rich textures. Experiments show that this model is competent for this issue and outperforms the state-of-the-a... | CBA | CBA | CAB | ABC | Selection 3 |
**A**: The concept of BEC was first introduced by Elias in 1955 InfThe **B**: Together with the binary symmetric channel (BSC), they are frequently used in coding theory and information theory because they are among the simplest channel models, and many problems in communication theory can be reduced to problems in a B... | CBA | ABC | ACB | BCA | Selection 4 |
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