Finding densest subgraphs is a fundamental problem in graph mining, with several applications in different fields. In this paper, we consider two variants of the problem of covering a graph with k densest subgraphs, w...
详细信息
We study recovery of amplitudes and nodes of a finite impulse train from noisy frequency samples. This problem is known as super-resolution under sparsity constraints and has numerous applications. An especially chall...
详细信息
We introduce and study constrained Markov Decision Processes (cMDPs) with anytime constraints. An anytime constraint requires the agent to never violate its budget at any point in time, almost surely. Although Markovi...
详细信息
We introduce and study constrained Markov Decision Processes (cMDPs) with anytime constraints. An anytime constraint requires the agent to never violate its budget at any point in time, almost surely. Although Markovian policies are no longer sufficient, we show that there exist optimal deterministic policies augmented with cumulative costs. In fact, we present a fixed-parameter tractable reduction from anytime-constrained cMDPs to unconstrained MDPs. Our reduction yields planning and learning algorithms that are time and sample-efficient for tabular cMDPs so long as the precision of the costs is logarithmic in the size of the cMDP. However, we also show that computing non-trivial approximately optimal policies is NP-hard in general. To circumvent this bottleneck, we design provable approximation algorithms that efficiently compute or learn an arbitrarily accurate approximately feasible policy with optimal value so long as the maximum supported cost is bounded by a polynomial in the cMDP or the absolute budget. Given our hardness results, our approximation guarantees are the best possible under worst-case analysis.
A novel semantic communication (SC)-assisted secrecy transmission framework is proposed. In particular, the legitimate transmitter (Tx) sends the superimposed semantic and bit stream to the legitimate receiver (Rx), w...
详细信息
ISBN:
(纸本)9781728190549
A novel semantic communication (SC)-assisted secrecy transmission framework is proposed. In particular, the legitimate transmitter (Tx) sends the superimposed semantic and bit stream to the legitimate receiver (Rx), where the information may be eavesdropped by the malicious node (EVE). As the EVE merely has the conventional bit-oriented communication structure, the semantic signal acts as the type of beneficial information-bearing artificial noise (AN), which not only keeps strictly confidential to the EVE but also interferes with the EVE. The ergodic (equivalent) secrecy rate over fading wiretap channels is maximized by jointly optimizing the transmit power, semantic-bit power splitting ratio, and the successive interference cancellation decoding order at the Tx, subject to both the instantaneous peak and long-term average power constraints. To address this non-convex problem, both the optimal and suboptimal algorithms are developed by employing the Lagrangian dual method and the successive convex approximation method, respectively. Numerical results show that the proposed SC-assisted secrecy transmission scheme can significantly enhance the physical layer security compared to the baselines using the conventional bit-oriented communication and no-information-bearing AN. It also shows that the proposed suboptimal algorithm can achieve a near-optimal performance.
We present an approximation algorithm for Weighted Tree Augmentation with approximation factor 1 + ln 2+ epsilon < 1.7. This is the first algorithm beating the longstanding factor of 2, which can be achieved throug...
详细信息
ISBN:
(纸本)9781665420556
We present an approximation algorithm for Weighted Tree Augmentation with approximation factor 1 + ln 2+ epsilon < 1.7. This is the first algorithm beating the longstanding factor of 2, which can be achieved through many standard techniques.
In this paper, we propose an accelerated version of Simultaneous Perturbation Stochastic approximation (Accelerated SPSA). This algorithm belongs to the class of methods used in derivative-free optimization and has pr...
详细信息
ISBN:
(数字)9781665451963
ISBN:
(纸本)9781665451963
In this paper, we propose an accelerated version of Simultaneous Perturbation Stochastic approximation (Accelerated SPSA). This algorithm belongs to the class of methods used in derivative-free optimization and has proven efficacy in the problems including significant non-statistical uncertainties. We focus on analysis of Accelerated SPSA in a non-stationary setting and consider the presence of unknown-but-bounded disturbances. Research on these problems covers many directions. However, in large-scale systems, efficiency still remains a concern. It gave rise to the research where acceleration represents an objective in the algorithm's design. This problem motivated us to extend our previous research on SPSA in the direction of acceleration. We show that the proposed new accelerated version converges faster than the initial one. The validation of the algorithm is preformed in a target tracking problem.
Counterfactual explanations shed light on the decisions of black-box models by explaining how an input can be altered to obtain a favourable decision from the model (e.g., when a loan application has been rejected). H...
详细信息
ISBN:
(纸本)1577358872
Counterfactual explanations shed light on the decisions of black-box models by explaining how an input can be altered to obtain a favourable decision from the model (e.g., when a loan application has been rejected). However, as noted recently, counterfactual explainers may lack robustness in the sense that a minor change in the input can cause a major change in the explanation. This can cause confusion on the user side and open the door for adversarial attacks. In this paper, we study some sources of non-robustness. While there are fundamental reasons for why an explainer that returns a single counterfactual cannot be robust in all instances, we show that some interesting robustness guarantees can be given by reporting multiple rather than a single counterfactual. Unfortunately, the number of counterfactuals that need to be reported for the theoretical guarantees to hold can be prohibitively large. We therefore propose an approximation algorithm that uses a diversity criterion to select a feasible number of most relevant explanations and study its robustness empirically. Our experiments indicate that our method improves the state-of-the-art in generating robust explanations, while maintaining other desirable properties and providing competitive computational performance.
In order to achieve fast and high precision force/pose control of on-orbit mission, the impedance control problem of dual-arm space robot auxiliary docking operation in orbit is studied. Firstly, by using the Lagrange...
详细信息
ISBN:
(数字)9798350373974
ISBN:
(纸本)9798350373981;9798350373974
In order to achieve fast and high precision force/pose control of on-orbit mission, the impedance control problem of dual-arm space robot auxiliary docking operation in orbit is studied. Firstly, by using the Lagrange method the dynamics equation of the closed chain hybrid system formed after the capture operation of the dual-arm space robot is established. And based on impedance control theory, a second-order linear impedance model and a second-order approximate environment model are established. Then, a supertwist sliding mode control algorithm based on the social spider optimization(SSO) algorithm is proposed. Finally, the Lyapunov stability determination verifies that the system is uniformly asymptotically stable. The simulation results show that the proposed control algorithm can simultaneously achieve high-precision force/pose control. The attitude control accuracy reaches 0.05 degrees, the position control accuracy reaches 0.001m, and the output force control accuracy reaches 0.5N. It can meet the task requirements of the auxiliary docking operation of the dual-arm space robot in orbit.
In budget-feasible mechanism design, a buyer wishes to procure a set of items of maximum value from self-interested rational players. We are given an item-set U and a nonnegative valuation function v : 2(U) (sic) R+. ...
详细信息
ISBN:
(纸本)9783959773096
In budget-feasible mechanism design, a buyer wishes to procure a set of items of maximum value from self-interested rational players. We are given an item-set U and a nonnegative valuation function v : 2(U) (sic) R+. Each item e is held by a player who incurs a private cost c(e) for supplying item e. The goal is to devise a truthful mechanism such that the total payment made to the players is at most some given budget B, and the value of the set returned is a good approximation to OPT := max {v(S) : c(S) <= B, S subset of U}. We call such a mechanism a budget-feasible mechanism. More generally, there may be additional side constraints requiring that the set returned lies in some downwards-monotone family I subset of 2(U). Budget-feasible mechanisms have been widely studied, but there are still significant gaps in our understanding of these mechanisms, both in terms of what kind of oracle access to the valuation is required to obtain good approximation ratios, and the best approximation ratio that can be achieved. We substantially advance the state of the art of budget-feasible mechanisms by devising mechanisms that are simpler, and also better, both in terms of requiring weaker oracle access and the approximation factors they obtain. For XOS valuations, we devise the first polytime O(1)-approximation budget-feasible mechanism using only demand oracles, and also significantly improve the approximation factor. For subadditive valuations, we give the first explicit construction of an O(1)-approximation mechanism, where previously only an existential result was known. We also introduce a fairly rich class of mechanism-design problems that we dub using the umbrella term generalized budget-feasible mechanism design, which allow one to capture payment constraints that are much-more nuanced than a single constraint on the total payment doled out. We demonstrate the versatility of our ideas by showing that our constructions can be adapted to yield approximation guarantees in
暂无评论