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IEEE Annual International Symposium Virtual Reality

作者： Voicu Popescu Elisha Sacks Zirui Zhang Jorge Vazquez Purdue University

ISBN: (数字)9798331536459

ISBN: (纸本)9798331536466

All-in-one VR headsets have limited rendering power which limits the complexity of the virtual environments (VEs) that can be used in VR applications. This paper describes a novel visibility algorithm for making complex VEs tractable on all-in-one VR headsets. Given a view segment, the algorithm finds the set of triangles visible as a camera translates on the view segment. When run on the perimeter of a user view region, the algorithm provides a quality approximation of the visible set from inside the view region. The visibility algorithm supports static and dynamic VEs, and it solves visibility with either triangle, particle, or object granularity. The visible sets yield output frames that are virtually indistinguishable from ground truth frames rendered from the original VEs.

关键词： Headphones Three-dimensional displays Heuristic algorithms Virtual environments User interfaces approximation algorithms Rendering (computer graphics) Cameras Complexity theory

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Quaternionic Minkowski Reduction and Its Application in Dual-Polarized MIMO Systems

Quaternionic Minkowski Reduction and Its Application in Dual...

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International ITG Conference on Source and Channel Coding (SCC)

作者： Sebastian Stern Cong Ling Cornelia Ott Robert F.H. Fischer Institute of Communications Engineering Ulm University Germany Department of Electrical and Electronic Engineering Imperial College London United Kingdom Institute of Communications and Navigation German Aerospace Center (DLR) Germany

ISBN: (数字)9798331522896

ISBN: (纸本)9798331522902

The task of finding the shortest vectors of a lattice that form a basis thereof is known as Minkowski reduction. In this work, Minkowski reduction is adapted to discrete subgroups of quaternionic spaces defined over the set of Hurwitz integers which constitutes a Euclidean subring of the (Hamilton) quaternions. Based on a quaternionic variant of Minkowski's greatest-common-divisor condition for suitable lattice vectors, a lattice-basis-reduction algorithm is derived. To that end, a basisupdate approach is presented which takes the non-commutativity of quaternionic multiplication into account. The reduction algorithm is finally applied in multi-user multiple-input/multipleoutput (MIMO) systems with dual-polarized antennas, where the quaternionic interference is handled by lattice-reduction-aided equalization. It is shown that quaternionic Minkowski reduction achieves significantly better results than state-of-the-art Lenstra-Lenstra-Lovász (LLL) reduction and that the successive minima of quaternionic lattices are approximated quite well.

关键词： Quaternions Lattices Interference approximation algorithms Vectors MIMO Encoding Antennas

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Algorithm Design for Continual Learning in IoT Networks

Algorithm Design for Continual Learning in IoT Networks

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shugang Hao Lingjie Duan Pillar of Engineering Systems and Design Singapore University of Technology and Design

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Continual learning (CL) is a new online learning technique over sequentially generated streaming data from different tasks, aiming to maintain a small forgetting loss on previously-learned tasks. Existing work focuses on reducing the forgetting loss under a given task sequence. However, if similar tasks continuously appear to the end time, the forgetting loss is still huge on prior distinct tasks. In practical IoT networks, an autonomous vehicle to sample data and learn different tasks can route and alter the order of task pattern at increased travelling cost. To our best knowledge, we are the first to study how to opportunistically route the testing object and alter the task sequence in CL. We formulate a new optimization problem and prove it NP-hard. We propose a polynomial-time algorithm to achieve approximation ratios of $\frac{3}{2}$ for underparameterized case and $\frac{3}{2} + {r^{1 - T}}$ for overparameterized case, respectively. Simulation results verify our algorithm’s close-to-optimum performance.

关键词： Continuing education Costs Simulation Signal processing algorithms Signal processing approximation algorithms Polynomials Speech processing Optimization Testing

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Heavy Traffic Analysis of Approximate Max-Weight Matching algorithms for Input-Queued Switches

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Performance Evaluation Review 2021年第3期48卷 109-110页

作者： Huang, Yu Huang, Longbo IIIS Tsinghua University Beijing China

In this paper, we propose a class of approximation algorithms for max-weight matching (MWM) policy for input-queued switches, called expected 1-APRX. We establish the state space collapse (SSC) result for expected 1-APRX, and characterize its queue length behavior in the heavy-traffic limit. © 2021 Copyright is held by the owner/author(s).

关键词： approximation algorithms

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Distributed Policy Evaluation with Local Updates over Time-Varying Communication Network

Distributed Policy Evaluation with Local Updates over Time-V...

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Annual Conference on Information Sciences and Systems (CISS)

作者： Matthew Crespo Chinwendu Enyioha Electrical and Computer Engineering University of Central Florida Orlando United States of America

ISBN: (数字)9798331513269

ISBN: (纸本)9798331513276

This paper studies a consensus-based policy evaluation algorithm in a cooperative team of heterogeneous learners. To improve each agent’s approximation of their value function, they each update their weight parameters, then perform consensus updates with neighboring agents over a dynamic communication network. We present the analysis of an efficient fully distributed algorithm for cooperatively evaluating and optimizing their value functions over a time-varying communication network in the average-reward setting. Our main result shows that, using this algorithm, the agents can approximate the true value function, with the approximation error dependent on the number of communication rounds and number of time steps it takes for the communication network to be connected. To validate the theoretical results, we present accompanying numerical experiments that show the theoretical error bounds are not only tight, but get tighter as the time steps required to guarantee network connectivity reduces.

关键词： Heuristic algorithms approximation algorithms approximation error Communication networks Distributed algorithms Time-varying systems

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Efficient Approximate Nearest Neighbor Search via Data-Adaptive Parameter Adjustment in Hierarchical Navigable Small Graphs

Efficient Approximate Nearest Neighbor Search via Data-Adapt...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Huijun Jin Jieun Lee Shengmin Piao Sangmin Seo Sein Kwon Sanghyun Park Computer Science Yonsei University Seoul Korea Artificial Intelligence Yonsei University Seoul Korea

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

Hierarchical Navigable Small World (HNSW) graphs are a state-of-the-art solution for approximate nearest neighbor search, widely applied in areas like recommendation systems, computer vision, and natural language processing. However, the effectiveness of the HNSW algorithm is constrained by its reliance on static parameter settings, which do not account for variations in data density and dimensionality across different datasets. This paper introduces Dynamic HNSW, an adaptive method that dynamically adjusts key parameters - such as the $M$ (number of connections per node) and ef (search depth) - based on both local data density and dimensionality of the dataset. The proposed approach improves flexibility and efficiency, allowing the graph to adapt to diverse data characteristics. Experimental results across multiple datasets demonstrate that Dynamic HNSW significantly reduces graph build time by up to 33.11% and memory usage by up to 32.44%, while maintaining comparable recall, thereby outperforming the conventional HNSW in both scalability and efficiency.

关键词： Learning systems Heuristic algorithms Scalability Memory management Europe Nearest neighbor methods approximation algorithms Natural language processing Tuning Recommender systems

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On Approximability of the Permanent of PSD Matrices 25

On Approximability of the Permanent of PSD Matrices

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Proceedings of the 57th Annual ACM Symposium on Theory of Computing

作者： Farzam Ebrahimnejad Ansh Nagda Shayan Oveis Gharan University of Washington Seattle USA University of California at Berkeley Berkeley USA

ISBN: (纸本)9798400715105

We study the complexity of approximating the permanent of a positive semidefinite matrix A∈ ℂn× *** first result is a new approximation algorithm for per(A) with approximation ratio e−(0.9999 + γ)n, exponentially improving upon the current best bound of e−(1+γ−o(1))n (Anari-Gurvits-Oveis Gharan-Saberi 2017, Yuan-Parrilo 2022). Here, γ ≈ 0.577 is Euler’s *** second result is a hardness result. We prove that it is NP-hard to approximate per(A) within a factor e−(γ−)n for any >0. This is the first exponential hardness of approximation for this problem. Along the way, we prove optimal hardness of approximation results for the ||·||2→ q “norm” problem of a matrix for all −1 < q < 2.

关键词： approximation algorithms

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PAC-Private algorithms

PAC-Private Algorithms

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IEEE Symposium on Security and Privacy

作者： Mayuri Sridhar Hanshen Xiao Srinivas Devadas MIT CSAIL Cambridge MA Purdue University/NVIDIA Research West Lafayette Indiana

ISBN: (数字)9798331522360

ISBN: (纸本)9798331522377

Provable privacy typically requires involved analysis and is often associated with unacceptable accuracy loss. While many empirical verification or approximation methods, such as Membership Inference Attacks (MIA) and Differential Privacy Auditing (DPA), have been proposed, these do not offer rigorous privacy guarantees. In this paper, we apply recently-proposed Probably Approximately Correct (PAC) Privacy to give formal, mechanized, simulation-based proofs for a range of practical, black-box algorithms: K-Means, Support Vector Machines (SVM), Principal Component Analysis (PCA) and Random Forests. To provide these proofs, we present a new simulation algorithm that efficiently determines anisotropic noise perturbation required for any given level of privacy. We provide a proof of correctness for this algorithm and demonstrate that anisotropic noise has substantive benefits over isotropic noise. Stable algorithms are easier to privatize, and we demonstrate privacy amplification resulting from introducing regularization in these algorithms; meaningful privacy guarantees are obtained with small losses in accuracy. We propose new techniques in order to reduce instability in algorithmic output and convert intractable geometric stability verification into efficient deterministic stability verification. Thorough experiments are included, and we validate our provable adversarial inference hardness against state-of-the-art empirical attacks.

关键词： Support vector machines Privacy Accuracy Closed box Anisotropic approximation algorithms Inference algorithms Picture archiving and communication systems Stability analysis Principal component analysis

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Methods and Software Tools for Converting Road Marking Line Segmentation Mask to Object Representation for Highly Automated Vehicles

Methods and Software Tools for Converting Road Marking Line ...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Danil Dolgov Alexander Dolgov Imil Khairullin Faculty of Information Systems and Technologies Ulyanovsk State Technical University Ulyanovsk Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

This paper describes the development of an algorithm for converting segmentation masks derived from neural networks into ordered sets of point coordinates representing road markings for highly automated vehicles (HAVs). Several methods are considered, including the nearest neighbor method, polynomial approximation, Hough transform, and parallel contouring. Performance tests and complexity analyses are performed for each method. The parallel contour method with dynamic search for opposite points was the most effective, demonstrating linear complexity and high accuracy in approximating road marking contours. This solution ensures efficient processing of large real-time datasets, critical for HAV navigation. The study integrates the algorithm into a unified system, combining segmentation with mask-to-line conversion, enhancing autonomous driving precision.

关键词： Industries Accuracy Navigation Roads Neural networks Software algorithms Transforms approximation algorithms Polynomials Real-time systems

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Property Testing of Curve Similarity

arXiv

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arXiv 2025年

作者： Afshani, Peyman Buchin, Maike Driemel, Anne Richter, Marena Wong, Sampson Department of Computer Science Aarhus University Denmark Faculty of Computer Science Ruhr University Bochum Germany Institute for Computer Science University of Bonn Germany Department of Computer Science University of Copenhagen Denmark

We propose sublinear algorithms for probabilistic testing of the discrete and continuous Fréchet distance—a standard similarity measure for curves. We assume the algorithm is given access to the input curves via a query oracle: a query returns the set of vertices of the curve that lie within a radius δ of a specified vertex of the other curve. The goal is to use a small number of queries to determine with constant probability whether the two curves are similar (i.e., their discrete Fréchet distance is at most δ) or they are ‘Ε-far’ (for 0 t/Ε log t/Ε ) queries and is given the value of t in advance. The second algorithm does not have explicit knowledge of the value of t and therefore needs to gain implicit knowledge of the straightness of the input curves through its queries. We show that the discrete Fréchet distance can still be tested using roughly O(t3 +t2 log n/Ε) queries ignoring logarithmic factors in t. Our algorithms work in a matrix representation of the input and may be of independent interest to matrix testing. Our algorithms use a mild uniform sampling condition that constrains the edge lengths of the curves, similar to a polynomially bounded aspect ratio. Applied to testing the continuous Fréchet distance of t-straight curves, our algorithms can be used for (1 + Ε′)-approximate testing using essentially the same bounds as stated above with an additional factor of poly(1/Ε′ ). Copyright © 2025, The Authors. All rights reserved.

关键词： approximation algorithms

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