arXiv subjects

Ning Cai

Publications and source records attributed to Ning Cai.

At least 19 recordsLinked to original sources

arXiv2026

Cryptographic and Information-theoretic Security Capacities for General Arbitrarily Varying Wiretap Channels

We compare the strong secrecy capacities of Arbitrarily Varying Wiretap Channels (AVWCs) and General Arbitrarily Varying Wiretap Channels (GAVWCs) with their capacities under semantic secrecy constraint and other equivalent cryptographic secrecy constraints. It turns out that the average error and strong secrecy capacity of an AVWC is always equal to its maximal error and semantic secrecy capacity. However, this equivalence does not hold for all general communication systems, and we prove this by a counterexample. We also show that, for the GAVWC, semantic security and the other cryptographic security measures considered achieve the same capacity values. Finally, we bound the gap between the strong secrecy capacity and the semantic secrecy capacity for the GAVWC. The gap vanishes if the choice of the jammer is sub-double-exponential with respect to the block length n, which gives a sufficient condition for the strong and semantic secrecy capacities to be equal for GAVWCs.

cs.IT↗

arXiv2026

Perfectly Fitting CDO Prices Across Tranches: A Theoretical Framework with Efficient Algorithms

This paper addresses a key challenge in CDO modeling: achieving a perfect fit to market prices across all tranches using a single, consistent model. The existence of such a perfect-fit model implies the absence of arbitrage among CDO tranches and is thus essential for unified risk management and the pricing of nonstandard credit derivatives. To address this central challenge, we face three primary difficulties: standard parametric models typically fail to achieve a perfect fit; the calibration of standard parametric models inherently relies on computationally intensive simulation-based optimization; and there is a lack of formal theory to determine when a perfect-fit model exists and, if it exists, how to construct it. We propose a theoretical framework to overcome these difficulties. We first introduce and define two compatibility levels of market prices: weak compatibility and strong compatibility. Specifically, market prices across all tranches are said to be weakly (resp. strongly) compatible if there exists a single model (resp. a single conditionally i.i.d. model) that perfectly fits these market prices. We then derive sufficient and necessary conditions for both levels of compatibility by establishing a relationship between compatibility and LP problems. Furthermore, under either condition, we construct a corresponding concrete copula model that achieves a perfect fit. Notably, our framework not only allows for efficient verification of weak compatibility and strong compatibility through LP problems but also facilitates the construction of the corresponding copula models that achieve a perfect fit, eliminating the need for simulation-based optimization. The practical applications of our framework are demonstrated in risk management and the pricing of nonstandard credit derivatives.

q-fin.RM↗

arXiv2025

MPRM: A Markov Path-based Rule Miner for Efficient and Interpretable Knowledge Graph Reasoning

Rule mining in knowledge graphs enables interpretable link prediction. However, deep learning-based rule mining methods face significant memory and time challenges for large-scale knowledge graphs, whereas traditional approaches, limited by rigid confidence metrics, incur high computational costs despite sampling techniques. To address these challenges, we propose MPRM, a novel rule mining method that models rule-based inference as a Markov chain and uses an efficient confidence metric derived from aggregated path probabilities, significantly lowering computational demands. Experiments on multiple datasets show that MPRM efficiently mines knowledge graphs with over a million facts, sampling less than 1% of facts on a single CPU in 22 seconds, while preserving interpretability and boosting inference accuracy by up to 11% over baselines.

cs.AI↗

arXiv2022

Temporal Variation Measure Analysis: An Improved Second-Order Difference Plot

In this study, an improved second-order difference plot is proposed to analyze the variability of heart rate variability. Although the variation of physiological status of cardiovascular system can be shown graphically by the second-order difference plot, the descriptive ability of existing indicators for this plot is insufficient. As a result, the physiological information contained in the second-order difference plot cannot be extracted adequately. Addressing the problem, the temporal variation measure analysis is presented to describe distribution patterns of scatter points in the second-order difference plot quantitatively and extract the acceleration information for variation of heart rate variability. Experiment results demonstrate the effectiveness of the temporal variation measure analysis. As a quantitative indicator, the temporal variation entropy is properly designed and successfully applied in the recognition and classification of the physiological statuses of the heart.

eess.SY↗

arXiv2022

On Clustering Trend in Language Evolution Based on Dynamical Behaviors of Multi-Agent Model

Computer model has been extensively adopted to overcome the time limitation of language evolution by transforming language theory into physical modeling mechanism, which helps to explore the general laws of the evolution. In this paper, a multi-agent model is designed to simulate the evolution process of language in human settlements, with the network topology being lattice. The language of each node in the lattice will evolve gradually under the influence of its own fixed evolutionary direction and neighbors. According to the computational experiment results, it is discovered that the state points of languages always converge into several clusters during evolution process, which gives us an insight into language evolution.

eess.SY↗

arXiv2021

On Novel Peer Review System for Academic Journals: Experimental Study Based on Social Computing

For improving the performance and effectiveness of peer review, a novel review system is proposed, based on analysis of peer review process for academic journals under a parallel model built via Monte Carlo method. The model can simulate the review, application and acceptance activities of the review systems, in a distributed manner. According to simulation experiments on two distinct review systems respectively, significant advantages manifest for the novel one.

cs.DL↗

arXiv2021

Universal classical-quantum superposition coding and universal classical-quantum multiple access channel coding

We derive universal classical-quantum superposition coding and universal classical-quantum multiple access channel code by using generalized packing lemmas for the type method. Using our classical-quantum universal superposition code, we establish the capacity region of a classical-quantum compound broadcast channel with degraded message sets. Our universal classical-quantum multiple access channel codes have two types of codes. One is a code with joint decoding and the other is a code with separate decoding. The former universally achieves corner points of the capacity region and the latter universally achieves general points of the capacity region. Combining the latter universal code with the existing result by Quantum Inf Process. 18, 246 (2019), we establish a single-letterized formula for the capacity region of a classical-quantum compound multiple access channel.

quant-ph↗

arXiv2020

Online Knowledge Distillation via Multi-branch Diversity Enhancement

Knowledge distillation is an effective method to transfer the knowledge from the cumbersome teacher model to the lightweight student model. Online knowledge distillation uses the ensembled prediction results of multiple student models as soft targets to train each student model. However, the homogenization problem will lead to difficulty in further improving model performance. In this work, we propose a new distillation method to enhance the diversity among multiple student models. We introduce Feature Fusion Module (FFM), which improves the performance of the attention mechanism in the network by integrating rich semantic information contained in the last block of multiple student models. Furthermore, we use the Classifier Diversification(CD) loss function to strengthen the differences between the student models and deliver a better ensemble result. Extensive experiments proved that our method significantly enhances the diversity among student models and brings better distillation performance. We evaluate our method on three image classification datasets: CIFAR-10/100 and CINIC-10. The results show that our method achieves state-of-the-art performance on these datasets.

cs.CV↗

arXiv2020

Message Transmission over Classical Quantum Channels with a Jammer with Side Information: Correlation as Resource, Common Randomness Generation

In this paper we analyze the capacity of a general model for arbitrarily varying classical-quantum channels (AVCQCs) when the sender and the receiver use correlation as a resource. In this general model, a jammer has side information about the channel input. We determine a single letter formula for the correlation assisted capacity. As an application of our main result, we determine the correlation assisted common randomness generation capacity. In this scenario the two channel users have access to correlation as a resource,and further use an AVCQC with an informed jammer for additional discussion. The goal is to create common randomness between the two channel users. We also analyze these capacity formulas when only a small number of signals from the correlation are available. For the correlation assisted common randomness generation capacity, we show an additional interesting property: For a sufficient amount of "public communication", common randomness generation capacity is Turing computable, however without this public communication constraint, the correlation assisted common randomness generation capacity is, in general, not Turing computable. Furthermore, we show that even without knowing the capacity formula of the deterministic capacity using maximal error criterion, we can show that it is impossible to evaluate the performance algorithmically on any current or future digital computer.

cs.IT↗

arXiv2020

Asymptotically Secure Network Code for Active Attacks and its Application to Network Quantum Key Distribution

When there exists a malicious attacker in the network, we need to be careful of eavesdropping and contamination. This problem is crucial for network communication when the network is realized by a partially trusted relay of quantum key distribution. We discuss the asymptotic rate in a linear network with the secrecy and robustness conditions when the above type of attacker exists. Also, under the same setting, we discuss the asymptotic rate in a linear network when we impose the secrecy condition alone. Then, we apply these results to the network composed of a partially trusted relay of quantum key distribution, which enables us to realize secure long-distance communication via short-distance quantum key distribution.

cs.IT↗

arXiv2020

Secure network code over one-hop relay network

When there exists a malicious attacker in the network, we need to consider the possibilities of eavesdropping and the contamination simultaneously. Under an acyclic broadcast network, the optimality of linear codes was shown when Eve is allowed to attack any $r$ edges. The optimality of linear codes is not shown under a different assumption for Eve. As a typical example of an acyclic unicast network, we focus on the one-hop relay network under the single transmission scheme by assuming that Eve attacks only one edge in each level. Surprisingly, as a result, we find that a non-linear code significantly improves the performance on the one-hop relay network over linear codes. That is, a non-liner code realizes the imperfect security on this model that cannot be realized by linear codes. This kind of superiority of a linear code still holds even with considering the effect of sequential error injection on information leakage.

cs.IT↗

arXiv2020

Reduction Theorem for Secrecy over Linear Network Code for Active Attacks

We discuss the effect of sequential error injection on information leakage under a network code. We formulate a network code for the single transmission setting and the multiple transmission setting. Under this formulation, we show that the eavesdropper cannot improve the power of eavesdropping by sequential error injection when the operations in the network are linear operations. We demonstrate the usefulness of this reduction theorem by applying a concrete example of network.

cs.IT↗

arXiv2019

On Performance of Peer Review for Academic Journals: Analysis Based on Distributed Parallel System

A simulation model based on parallel systems is established, aiming to explore the relation between the number of submissions and the overall standard of academic journals within a similar discipline under peer review. The model can effectively simulate the submission, review, and acceptance behaviors of academic journals in a distributed manner. According to the simulation experiments, it could possibly happen that the overall standard of academic journals deteriorates due to excessive submissions.

cs.DL↗

arXiv2019

Computing the Classical-Quantum channel capacity: experiments on a Blahut-Arimoto type algorithm and an approximate solution for the binary inputs, two-dimensional outputs channel

In our previous work, we presented a Blahut-Arimoto type algorithm for computing the discrete memoryless (DM) classical-quantum channel capacity. And the speed of convergence is analyzed. In this paper, we present numerical experiment to show that the algorithm converged much faster than the theoretical prediction. Also we present an explicit approximate solution for the binary inputs, two dimensional outputs classical-quantum channel, which has an error within $3\times10^{-4}$

quant-ph↗

arXiv2019

Adaptive Guaranteed-Performance Consensus Control for Multiagent Systems With an Adjustable Convergence Speed

Adaptive guaranteed-performance consensus control problems for multi-agent systems are investigated, where the adjustable convergence speed is discussed. This paper firstly proposes a novel adaptive guaranteed-performance consensus protocol, where the communication weights can be adaptively regulated. By the state space decomposition method and the stability theory, sufficient conditions for guaranteed-performance consensus are obtained, as well as the guaranteed-performance cost. Moreover, since the convergence speed is usually adjusted by changing the algebraic connectivity in existing works, which increases the communication burden and the load of the controller, and the system topology is always given in practical applications, the lower bound of the convergence coefficient for multi-agent systems with the adaptive guaranteed-performance consensus protocol is deduced, which is linearly adjustable approximately by changing the adaptive control gain. Finally, simulation examples are introduced to demonstrate theoretical results.

eess.SY↗

arXiv2019

A Blahut-Arimoto Type Algorithm for Computing Classical-Quantum Channel Capacity

Based on Arimoto's work in 1978, we propose an iterative algorithm for computing the capacity of a discrete memoryless classical-quantum channel with a finite input alphabet and a finite dimensional output, which we call the Blahut-Arimoto algorithm for classical-quantum channel, and an input cost constraint is considered. We show that to reach $\varepsilon$ accuracy, the iteration complexity of the algorithm is up bounded by $\frac{\log n\log\varepsilon}{\varepsilon}$ where $n$ is the size of the input alphabet. In particular, when the output state $\{ρ_x\}_{x\in \mathcal{X}}$ is linearly independent in complex matrix space, the algorithm has a geometric convergence. We also show that the algorithm reaches an $\varepsilon$ accurate solution with a complexity of $O(\frac{m^3\log n\log\varepsilon}{\varepsilon})$, and $O(m^3\log\varepsilon\log_{(1-δ)}\frac{\varepsilon}{D(p^*||p^{N_0})})$ in the special case, where $m$ is the output dimension and $D(p^*||p^{N_0})$ is the relative entropy of two distributions and $δ$ is a positive number.

quant-ph↗

arXiv2018

Secrecy and Robustness for Active Attack in Secure Network Coding and its Application to Network Quantum Key Distribution

In network coding, we discuss the effect of sequential error injection on information leakage. We show that there is no improvement when the operations in the network are linear operations. However, when the operations in the network contains non-linear operations, we find a counterexample to improve Eve's obtained information. Furthermore, we discuss the asymptotic rate in a linear network under the secrecy and robustness conditions as well as under the secrecy condition alone. Finally, we apply our results to network quantum key distribution, which clarifies the type of network that enables us to realize secure long distance communication via short distance quantum key distribution.

cs.IT↗

arXiv2018

Message Transmission over Classical Quantum Channels with a Jammer with Side Information: Message Transmission Capacity and Resources

In this paper we propose a new model for arbitrarily varying classical-quantum channels. In this model a jammer has side information. We consider two scenarios. In the first scenario the jammer knows the channel input, while in the second scenario the jammer knows both the channel input and the message. The transmitter and receiver share a secret random key with a vanishing key rate. We determine the capacity for both average and maximum error criteria for both scenarios. We also establish the strong converse. We show that all these corresponding capacities are equal, which means that additionally revealing the message to the jammer does not change the capacity.

cs.IT↗