IA Scholar Query: The connectivity of acyclic orientation graphs.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgSat, 01 Oct 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440Isadore M. Singer (1924–2021) In Memoriam Part 1: Scientific Works
https://scholar.archive.org/work/aejx3oq2lvch5gdpwoqpzzlbqe
Robert Bryant, Jean-Michel Bismut, Jeff Cheeger, Phillip Griffiths, Simon Donaldson, Nigel Hitchin, H Blaine Lawson, Michail Gromov, Adam Marcus, Daniel Spielman, Nikhil Srivastava, Edward Wittenwork_aejx3oq2lvch5gdpwoqpzzlbqeSat, 01 Oct 2022 00:00:00 GMTImproving Attention-Based Interpretability of Text Classification Transformers
https://scholar.archive.org/work/djtxsnpc7fd3hjtyzdro3lxqzq
Transformers are widely used in NLP, where they consistently achieve state-of-the-art performance. This is due to their attention-based architecture, which allows them to model rich linguistic relations between words. However, transformers are difficult to interpret. Being able to provide reasoning for its decisions is an important property for a model in domains where human lives are affected, such as hate speech detection and biomedicine. With transformers finding wide use in these fields, the need for interpretability techniques tailored to them arises. The effectiveness of attention-based interpretability techniques for transformers in text classification is studied in this work. Despite concerns about attention-based interpretations in the literature, we show that, with proper setup, attention may be used in such tasks with results comparable to state-of-the-art techniques, while also being faster and friendlier to the environment. We validate our claims with a series of experiments that employ a new feature importance metric.Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakaswork_djtxsnpc7fd3hjtyzdro3lxqzqThu, 22 Sep 2022 00:00:00 GMTEfficiently Reconfiguring a Connected Swarm of Labeled Robots
https://scholar.archive.org/work/fpyfg4ykzjgmtev2hdmxtiotfu
When considering motion planning for a swarm of n labeled robots, we need to rearrange a given start configuration into a desired target configuration via a sequence of parallel, continuous, collision-free robot motions. The objective is to reach the new configuration in a minimum amount of time; an important constraint is to keep the swarm connected at all times. Problems of this type have been considered before, with recent notable results achieving constant stretch for not necessarily connected reconfiguration: If mapping the start configuration to the target configuration requires a maximum Manhattan distance of d, the total duration of an overall schedule can be bounded to 𝒪(d), which is optimal up to constant factors. However, constant stretch could only be achieved if disconnected reconfiguration is allowed, or for scaled configurations (which arise by increasing all dimensions of a given object by the same multiplicative factor) of unlabeled robots. We resolve these major open problems by (1) establishing a lower bound of Ω(√(n)) for connected, labeled reconfiguration and, most importantly, by (2) proving that for scaled arrangements, constant stretch for connected reconfiguration can be achieved. In addition, we show that (3) it is NP-hard to decide whether a makespan of 2 can be achieved, while it is possible to check in polynomial time whether a makespan of 1 can be achieved.Sándor P. Fekete, Peter Kramer, Christian Rieck, Christian Scheffer, Arne Schmidtwork_fpyfg4ykzjgmtev2hdmxtiotfuThu, 22 Sep 2022 00:00:00 GMTLiesel: A Probabilistic Programming Framework for Developing Semi-Parametric Regression Models and Custom Bayesian Inference Algorithms
https://scholar.archive.org/work/vb7nf7vddvasxkfipj52u4qobm
Liesel is a probabilistic programming framework focusing on but not limited to semi-parametric regression. It comprises a graph-based model building library, a Markov chain Monte Carlo (MCMC) library with support for modular inference algorithms combining multiple kernels (both implemented in Python), and an R interface (RLiesel) for the configuration of semi-parametric regression models. Each component can be used independently of the others, e.g. the MCMC library also works with third-party model implementations. Our goal with Liesel is to facilitate a new research workflow in computational statistics: In a first step, the researcher develops a model graph with pre-implemented and well-tested building blocks as a base model, e.g. using RLiesel. Then, the graph can be manipulated to incorporate new research ideas, before the MCMC library can be used to run and analyze a default or user-defined MCMC procedure. The researcher has the option to combine powerful MCMC algorithms such as the No U-Turn Sampler (NUTS) with self-written kernels. Various tools for chain post-processing and diagnostics are also provided. Considering all its components, Liesel enables efficient and reliable statistical research on complex models and estimation algorithms. It depends on JAX as a numerical computing library. This way, it can benefit from the latest machine learning technology such as automatic differentiation, just-in-time (JIT) compilation, and the use of high-performance computing devices such as tensor processing units (TPUs).Hannes Riebl, Paul F.V. Wiemann, Thomas Kneibwork_vb7nf7vddvasxkfipj52u4qobmThu, 22 Sep 2022 00:00:00 GMTThe graph structure of two-player games
https://scholar.archive.org/work/nlqlfp2ownc3jl52dsgpbt2upa
In this paper we analyse two-player games by their response graphs. The response graph has nodes which are strategy profiles, with an arc between profiles if they differ in the strategy of a single player, with the direction of the arc indicating the preferred option for that player. Response graphs, and particularly their sink strongly connected components, play an important role in modern techniques in evolutionary game theory and multi-agent learning. We show that the response graph is a simple and well-motivated model of strategic interaction which captures many non-trivial properties of a game, despite not depending on cardinal payoffs. We characterise the games which share a response graph with a zero-sum or potential game respectively, and demonstrate a duality between these sets. This allows us to understand the influence of these properties on the response graph. The response graphs of Matching Pennies and Coordination are shown to play a key role in all two-player games: every non-iteratively-dominated strategy takes part in a subgame with these graph structures. As a corollary, any game sharing a response graph with both a zero-sum game and potential game must be dominance-solvable. Finally, we classify the response graphs of small games, and show how our taxonomy can be used to understand games which appear in well-known textbooks.Oliver Biggar, Iman Shameswork_nlqlfp2ownc3jl52dsgpbt2upaWed, 21 Sep 2022 00:00:00 GMTOn the positivity of twisted L^2-torsion for 3-manifolds
https://scholar.archive.org/work/fgxf4gly7vejdap3opncweed34
For any compact orientable irreducible 3-manifold N with empty or incompressible toral boundary, the twisted L^2-torsion is a non-negative function defined on the representation variety Hom(π_1(N),SL(n,ℂ)). The paper shows that if N has infinite fundamental group, then the L^2-torsion function is strictly positive. Moreover, this torsion function is continuous when restricted to the subvariety of upper triangular representations.Jianru Duanwork_fgxf4gly7vejdap3opncweed34Wed, 21 Sep 2022 00:00:00 GMTPHM SURVEY: Implementation of Prognostic Methods for Monitoring Industrial Systems
https://scholar.archive.org/work/kemxmxr7ezfg3egcfmxmt73j6e
Prognostics and Health Management (commonly called PHM) is a field that focuses on the degradation mechanisms of systems in order to estimate their health status, anticipate their failure and optimize their maintenance. PHM uses methods, tools and algorithms for monitoring, anomaly detection, cause diagnosis, prognosis of the remaining useful life (RUL) and maintenance optimization. It allows for permanently monitoring the health of the system and provides operators and managers with relevant information to decide on actions to be taken to maintain the system in optimal operational conditions. This paper aims to present the emergence of the PHM thematically to describe the subjacent processes, particularly prognosis, how it supplies the different maintenance strategies and to explain the benefits that can be anticipated. More specifically, this paper establishes a state of the art in prognostic methods used today in the PHM strategy. In addition, this paper shows the multitude of possible prognostic approaches and the choice of one among them that will help to provide a framework for industrial companies.Abdenour Soualhi, Mourad Lamraoui, Bilal Elyousfi, Hubert Razikwork_kemxmxr7ezfg3egcfmxmt73j6eWed, 21 Sep 2022 00:00:00 GMTRoot polytopes, tropical types, and toric edge ideals
https://scholar.archive.org/work/cvbnyr3xvba55jghra3fuqtgae
We consider arrangements of tropical hyperplanes where the apices of the hyperplanes are taken to infinity in certain directions. Such an arrangement defines a decomposition of Euclidean space where a cell is determined by its 'type' data, analogous to the covectors of an oriented matroid. By work of Develin-Sturmfels and Fink-Rincón, these 'tropical complexes' are dual to (regular) subdivisions of root polytopes, which in turn are in bijection with mixed subdivisions of certain generalized permutohedra. Extending previous work with Joswig-Sanyal, we show how a natural monomial labeling of these complexes describes polynomial relations (syzygies) among 'type ideals' which arise naturally from the combinatorial data of the arrangement. In particular, we show that the cotype ideal is Alexander dual to a corresponding initial ideal of the lattice ideal of the underlying root polytope. This leads to novel ways of studying algebraic properties of various monomial and toric ideals, as well as relating them to combinatorial and geometric properties. In particular, our methods of studying the dimension of the tropical complex leads to new formulas for homological invariants of toric edge ideals of bipartite graphs, which have been extensively studied in the commutative algebra community.Ayah Almousa, Anton Dochtermann, Ben Smithwork_cvbnyr3xvba55jghra3fuqtgaeTue, 20 Sep 2022 00:00:00 GMTSemantic-based Pre-training for Dialogue Understanding
https://scholar.archive.org/work/ndfb2nt7hngqhmxciyhrqaaqnq
Pre-trained language models have made great progress on dialogue tasks. However, these models are typically trained on surface dialogue text, thus are proven to be weak in understanding the main semantic meaning of a dialogue context. We investigate Abstract Meaning Representation (AMR) as explicit semantic knowledge for pre-training models to capture the core semantic information in dialogues during pre-training. In particular, we propose a semantic-based pre-training framework that extends the standard pre-training framework (Devlin et al., 2019) by three tasks for learning 1) core semantic units, 2) semantic relations and 3) the overall semantic representation according to AMR graphs. Experiments on the understanding of both chit-chats and task-oriented dialogues show the superiority of our model. To our knowledge, we are the first to leverage a deep semantic representation for dialogue pre-training.Xuefeng Bai, Linfeng Song, Yue Zhangwork_ndfb2nt7hngqhmxciyhrqaaqnqMon, 19 Sep 2022 00:00:00 GMTList-avoiding orientations
https://scholar.archive.org/work/wumd5qdo3zavlkqticm5nog6gq
Given a graph G with a set F(v) of forbidden values at each v ∈ V(G), an F-avoiding orientation of G is an orientation in which deg^+(v) ∉F(v) for each vertex v. Akbari, Dalirrooyfard, Ehsani, Ozeki, and Sherkati conjectured that if |F(v)| < 1/2 deg(v) for each v ∈ V(G), then G has an F-avoiding orientation, and they showed that this statement is true when 1/2 is replaced by 1/4. In this paper, we take a step toward this conjecture by proving that if |F(v)| < ⌊1/3 deg(v) ⌋ for each vertex v, then G has an F-avoiding orientation. Furthermore, we show that if the maximum degree of G is subexponential in terms of the minimum degree, then this coefficient of 1/3 can be increased to √(2) - 1 - o(1) ≈ 0.414. Our main tool is a new sufficient condition for the existence of an F-avoiding orientation based on the Combinatorial Nullstellensatz of Alon and Tarsi.Peter Bradshaw, Yaobin Chen, Hao Ma, Bojan Mohar, Hehui Wuwork_wumd5qdo3zavlkqticm5nog6gqMon, 19 Sep 2022 00:00:00 GMTAdopting Automated Bug Assignment in Practice: A Longitudinal Case Study at Ericsson
https://scholar.archive.org/work/l3klje4davg7rmjyqfi5nochxi
The continuous inflow of bug reports is a considerable challenge in large development projects. Inspired by contemporary work on mining software repositories, we designed a prototype bug assignment solution based on machine learning in 2011-2016. The prototype evolved into an internal Ericsson product, TRR, in 2017-2018. TRR's first bug assignment without human intervention happened in April 2019. Our study evaluates the adoption of TRR within its industrial context at Ericsson. Moreover, we investigate 1) how TRR performs in the field, 2) what value TRR provides to Ericsson, and 3) how TRR has influenced the ways of working. We conduct an industrial case study combining interviews with TRR stakeholders, minutes from sprint planning meetings, and bug tracking data. The data analysis includes thematic analysis, descriptive statistics, and Bayesian causal analysis. TRR is now an incorporated part of the bug assignment process. Considering the abstraction levels of the telecommunications stack, high-level modules are more positive while low-level modules experienced some drawbacks. On average, TRR automatically assigns 30% of the incoming bug reports with an accuracy of 75%. Auto-routed TRs are resolved around 21% faster within Ericsson, and TRR has saved highly seasoned engineers many hours of work. Indirect effects of adopting TRR include process improvements, process awareness, increased communication, and higher job satisfaction. TRR has saved time at Ericsson, but the adoption of automated bug assignment was more intricate compared to similar endeavors reported from other companies. We primarily attribute the difference to the very large size of the organization and the complex products. Key facilitators in the successful adoption include a gradual introduction, product champions, and careful stakeholder analysis.Markus Borg, Leif Jonsson, Emelie Engström, Béla Bartalos, Attila Szabówork_l3klje4davg7rmjyqfi5nochxiMon, 19 Sep 2022 00:00:00 GMTToric Ideals of Characteristic Imsets via Quasi-Independence Gluing
https://scholar.archive.org/work/meozrjyxk5fgnmc5nrakxfqqou
Characteristic imsets are 0-1 vectors which correspond to Markov equivalence classes of directed acyclic graphs. The study of their convex hull, named the characteristic imset polytope, has led to new and interesting geometric perspectives on the important problem of causal discovery. In this paper we begin the study of the associated toric ideal. We develop a new generalization of the toric fiber product, which we call a quasi-independence gluing, and show that under certain combinatorial homogeneity conditions, one can iteratively compute a Gr\"obner basis via lifting. For faces of the characteristic imset polytope associated to trees, we apply this technique to compute a Gr\"obner basis for the associated toric ideal. We end with a study of the characteristic ideal of the cycle and propose directions for future work.Benjamin Hollering, Joseph Johnson, Irem Portakal, Liam Soluswork_meozrjyxk5fgnmc5nrakxfqqouMon, 19 Sep 2022 00:00:00 GMTWFA-IRL: Inverse Reinforcement Learning of Autonomous Behaviors Encoded as Weighted Finite Automata
https://scholar.archive.org/work/4hfjmi2c3vg35lvlgglcf5atve
This paper presents a method for learning logical task specifications and cost functions from demonstrations. Constructing specifications by hand is challenging for complex objectives and constraints in autonomous systems. Instead, we consider demonstrated task executions, whose logic structure and transition costs need to be inferred by an autonomous agent. We employ a spectral learning approach to extract a weighted finite automaton (WFA), approximating the unknown task logic. Thereafter, we define a product between the WFA for high-level task guidance and a labeled Markov decision process for low-level control. An inverse reinforcement learning (IRL) problem is considered to learn a cost function by backpropagating the loss between agent and expert behaviors through the planning algorithm. Our proposed model, termed WFA-IRL, is capable of generalizing the execution of the inferred task specification in a suite of MiniGrid environments.Tianyu Wang, Nikolay Atanasovwork_4hfjmi2c3vg35lvlgglcf5atveMon, 19 Sep 2022 00:00:00 GMTAn Interactive Knowledge-based Multi-objective Evolutionary Algorithm Framework for Practical Optimization Problems
https://scholar.archive.org/work/4rnpwf2xerhr3ptwuee5luz4ee
Experienced users often have useful knowledge and intuition in solving real-world optimization problems. User knowledge can be formulated as inter-variable relationships to assist an optimization algorithm in finding good solutions faster. Such inter-variable interactions can also be automatically learned from high-performing solutions discovered at intermediate iterations in an optimization run - a process called innovization. These relations, if vetted by the users, can be enforced among newly generated solutions to steer the optimization algorithm towards practically promising regions in the search space. Challenges arise for large-scale problems where the number of such variable relationships may be high. This paper proposes an interactive knowledge-based evolutionary multi-objective optimization (IK-EMO) framework that extracts hidden variable-wise relationships as knowledge from evolving high-performing solutions, shares them with users to receive feedback, and applies them back to the optimization process to improve its effectiveness. The knowledge extraction process uses a systematic and elegant graph analysis method which scales well with number of variables. The working of the proposed IK-EMO is demonstrated on three large-scale real-world engineering design problems. The simplicity and elegance of the proposed knowledge extraction process and achievement of high-performing solutions quickly indicate the power of the proposed framework. The results presented should motivate further such interaction-based optimization studies for their routine use in practice.Abhiroop Ghosh, Kalyanmoy Deb, Erik Goodman, Ronald Averillwork_4rnpwf2xerhr3ptwuee5luz4eeSun, 18 Sep 2022 00:00:00 GMTToric Promotion
https://scholar.archive.org/work/f3c6vokm6fbfjfncswi3iskara
We introduce toric promotion as a cyclic analogue of Schützenberger's promotion operator. Toric promotion acts on the set of labelings of a graph G. We discuss connections between toric promotion and previously-studied notions such as toric posets and friends-and-strangers graphs. Our main theorem provides a surprisingly simple description of the orbit structure of toric promotion when G is a forest.Colin Defantwork_f3c6vokm6fbfjfncswi3iskaraSun, 18 Sep 2022 00:00:00 GMTRapid and fully automated blood vasculature analysis in 3D light-sheet image volumes of different organs
https://scholar.archive.org/work/s7u7uy6kbvbahm3dkbqpgmn7xu
Blood vasculature represents a complex network of vessels with varying lengths and diameters that are precisely organized in space to allow proper tissue function. Light-sheet fluorescence microscopy (LSFM) is very useful to generate tomograms of tissue vasculature with high spatial accuracy. Yet, quantitative LSFM analysis is still cumbersome and available methods are restricted to single organs and advanced computing hardware. Here, we introduce VesselExpress, an automated software that reliably analyzes six characteristic vascular network parameters including vessel diameter in LSFM data on average computing hardware. VesselExpress is ~100 times faster than other existing vessel analysis tools, requires no user interaction, integrates batch processing, and parallelization. Employing an innovative dual Frangi filter approach we show that obesity induces a large-scale modulation of brain vasculature in mice and that seven other major organs differ strongly in their 3D vascular makeup. Hence, VesselExpress transforms LSFM from an observational to an analytical working tool.Philippa Spangenberg, Nina Hagemann, Anthony Squire, Nils Foerster, Sascha D. Krauss, Yachao Qi, Ayan Mohamud yusuf, Jing Wang, Anika Grueneboom, Lennart Kowitz, Sebastian Korste, Matthias Totzeck, Zuelal Cibir, Ali Ata Tuz, Vikramjeet Singh, Devon Siemes, Laura Struensee, Daniel R. Engel, Peter Ludewig, Luiza M.N. Melo, Iris Helfrich, Jianxu Chen, Matthias Gunzer, Dirk M. Hermann, Axel Mosigwork_s7u7uy6kbvbahm3dkbqpgmn7xuSat, 17 Sep 2022 00:00:00 GMTA Trust-Based Model for Secure Routing against RPL Attacks in Internet of Things
https://scholar.archive.org/work/qkljy4yqyrb6bj5amnbpot4ozq
In IoT networks, the de facto Routing Protocol for Low Power and Lossy Networks (RPL) is vulnerable to various attacks. Routing attacks in RPL-based IoT are becoming critical with the increase in the number of IoT applications and devices globally. To address routing attacks in RPL-based IoT, several security solutions have been proposed in literature, such as machine learning techniques, intrusion detection systems, and trust-based approaches. Studies show that trust-based security for IoT is feasible due to its simple integration and resource-constrained nature of smart devices. Existing trust-based solutions have insufficient consideration of nodes' mobility and are not evaluated for dynamic scenarios to satisfy the requirements of smart applications. This research work addresses the Rank and Blackhole attacks in RPL considering the static as well as mobile nodes in IoT. The proposed Security, Mobility, and Trust-based model (SMTrust) relies on carefully chosen trust factors and metrics, including mobility-based metrics. The evaluation of the proposed model through simulation experiments shows that SMTrust performs better than the existing trust-based methods for securing RPL. The improvisation in terms of topology stability is 46%, reduction in packet loss rate is 45%, and 35% increase in throughput, with only 2.3% increase in average power consumption.Syeda Mariam Muzammal, Raja Kumar Murugesan, Noor Zaman Jhanjhi, Mamoona Humayun, Ashraf Osman Ibrahim, Abdelzahir Abdelmaboudwork_qkljy4yqyrb6bj5amnbpot4ozqSat, 17 Sep 2022 00:00:00 GMTA (1.5+ϵ)-Approximation Algorithm for Weighted Connectivity Augmentation
https://scholar.archive.org/work/jievulsebfbl3mxmrihu5wnu7u
Connectivity augmentation problems are among the most elementary questions in Network Design. Many of these problems admit natural 2-approximation algorithms, often through various classic techniques, whereas it remains open whether approximation factors below 2 can be achieved. One of the most basic examples thereof is the Weighted Connectivity Augmentation Problem (WCAP). In WCAP, one is given an undirected graph together with a set of additional weighted candidate edges, and the task is to find a cheapest set of candidate edges whose addition to the graph increases its edge-connectivity. We present a (1.5+ε)-approximation algorithm for WCAP, showing for the first time that factors below 2 are achievable. On a high level, we design a well-chosen local search algorithm, inspired by recent advances for Weighted Tree Augmentation. To measure progress, we consider a directed weakening of WCAP and show that it has highly structured planar solutions. Interpreting a solution of the original problem as one of this directed weakening allows us to describe local exchange steps in a clean and algorithmically amenable way. Leveraging these insights, we show that we can efficiently search for good exchange steps within a component class for link sets that is closely related to bounded treewidth subgraphs of circle graphs. Moreover, we prove that an optimum solution can be decomposed into smaller components, at least one of which leads to a good local search step as long as we did not yet achieve the claimed approximation guarantee.Vera Traub, Rico Zenklusenwork_jievulsebfbl3mxmrihu5wnu7uFri, 16 Sep 2022 00:00:00 GMTOrienting undirected phylogenetic networks
https://scholar.archive.org/work/hhlpfdc3jvfs7fkls5sbxcoggy
This paper studies the relationship between undirected (unrooted) and directed (rooted) phylogenetic networks. We describe a polynomial-time algorithm for deciding whether an undirected nonbinary phylogenetic network, given the locations of the root and reticulation vertices, can be oriented as a directed nonbinary phylogenetic network. Moreover, we characterize when this is possible and show that, in such instances, the resulting directed nonbinary phylogenetic network is unique. In addition, without being given the location of the root and the reticulation vertices, we describe an algorithm for deciding whether an undirected binary phylogenetic network N can be oriented as a directed binary phylogenetic network of a certain class. The algorithm is fixed-parameter tractable (FPT) when the parameter is the level of N and is applicable to classes of directed phylogenetic networks that satisfy certain conditions. As an example, we show that the well-studied class of binary tree-child networks satisfies these conditions.Katharina T. Huber, Leo van Iersel, Remie Janssen, Mark Jones, Vincent Moulton, Yukihiro Murakami, Charles Semplework_hhlpfdc3jvfs7fkls5sbxcoggyFri, 16 Sep 2022 00:00:00 GMTWorkflow-based Fast Data-driven Predictive Control with Disturbance Observer in Cloud-edge Collaborative Architecture
https://scholar.archive.org/work/m6vg7uufmrezdfaehqofmfemjq
Data-driven predictive control (DPC) has been studied and used in various scenarios, since it could generate the predicted control sequence only relying on the historical input and output data. Recently, based on cloud computing, data-driven predictive cloud control system (DPCCS) has been proposed with the advantage of sufficient computational resources. However, the existing computation mode of DPCCS is centralized. This computation mode could not utilize fully the computing power of cloud computing, of which the structure is distributed. Thus, the computation delay could not been reduced and still affects the control quality. In this paper, a novel cloud-edge collaborative containerised workflow-based DPC system with disturbance observer (DOB) is proposed, to improve the computation efficiency and guarantee the control accuracy. First, a construction method for the DPC workflow is designed, to match the distributed processing environment of cloud computing. But the non-computation overheads of the workflow tasks are relatively high. Therefore, a cloud-edge collaborative control scheme with DOB is designed. The low-weight data could be truncated to reduce the non-computation overheads. Meanwhile, we design an edge DOB to estimate and compensate the uncertainty in cloud workflow processing, and obtain the composite control variable. The UUB stability of the DOB is also proved. Third, to execute the workflow-based DPC controller and evaluate the proposed cloud-edge collaborative control scheme with DOB in the real cloud environment, we design and implement a practical workflow-based cloud control experimental system based on container technology. Finally, a series of evaluations show that, the computation times are decreased by 45.19% and 74.35% for two real-time control examples, respectively, and by at most 85.10% for a high-dimension control example.Runze Gao, Qiwen Li, Li Dai, Yufeng Zhan, Yuanqing Xiawork_m6vg7uufmrezdfaehqofmfemjqFri, 16 Sep 2022 00:00:00 GMT