Filters








562,399 Hits in 5.1 sec

Online selection of intervals and t -intervals

Unnar Th. Bachmann, Magnús M. Halldórsson, Hadas Shachnai
2013 Information and Computation  
We consider the problems of online selection of intervals and t-intervals, which show up in Video-on-Demand services, high speed networks and molecular biology, among others.  ...  We derive lower bounds and (almost) matching upper bounds on the competitive ratios of randomized algorithms for selecting intervals, 2-intervals and tintervals, for any t > 2.  ...  The competitive ratio of A is defined as sup σ OP T (σ) A(σ) , where σ is an input sequence, and OP T (σ), A(σ) are the number of t-intervals selected by OP T and A, respectively.  ... 
doi:10.1016/j.ic.2013.10.004 fatcat:zlo6ighaqbgkjkc3vugwb5hjqm

Online Selection of Intervals and t-Intervals [chapter]

Unnar Th. Bachmann, Magnús M. Halldórsson, Hadas Shachnai
2010 Lecture Notes in Computer Science  
We consider the problems of online selection of intervals and t-intervals, which show up in Video-on-Demand services, high speed networks and molecular biology, among others.  ...  We derive lower bounds and (almost) matching upper bounds on the competitive ratios of randomized algorithms for selecting intervals, 2-intervals and tintervals, for any t > 2.  ...  The competitive ratio of A is defined as sup σ OP T (σ) A(σ) , where σ is an input sequence, and OP T (σ), A(σ) are the number of t-intervals selected by OP T and A, respectively.  ... 
doi:10.1007/978-3-642-13731-0_36 fatcat:w5ytdj6drbdpllcvppfjgoiccy

Online Control of the False Coverage Rate and False Sign Rate [article]

Asaf Weinstein, Aaditya Ramdas
2019 arXiv   pre-print
Last, all of our methodology applies equally well to online FCR control for prediction intervals, having particular implications for assumption-free selective conformal inference.  ...  In the online setting, there is an infinite sequence of fixed unknown parameters θ_t ordered by time.  ...  the CI for θ t is dependent only on X t and independent of all other X i , and so is the interval if constructed.  ... 
arXiv:1905.01059v1 fatcat:lm5clvg2kzdr7eo5er5zuzrhcu

Online Retweet Recommendation with Item Count Limits

Xiaoqi Zhao, Keishi Tajima
2014 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)  
In order to help the management of such Twitter accounts, we developed a system that reads a sequence of tweets from the friends one by one, and select a given number of (or less) tweets in an online (  ...  The former two are truly online algorithms and the latter two are near-online algorithms.  ...  In other words,D ′ (u, T ) is the top-c tweets posted by the friends of u during T . r(u, T ) represents the ratio of total value of tweets selected by an online algorithm and by the optimal offline algorithm  ... 
doi:10.1109/wi-iat.2014.45 dblp:conf/webi/ZhaoT14 fatcat:fcxxcprltvho3lca4cedsjhufi

Computing the Median with Uncertainty

Tomás Feder, Rajeev Motwani, Rina Panigrahy, Chris Olston, Jennifer Widom
2003 SIAM journal on computing (Print)  
We focus on the selection function f which returns the value of the kth smallest argument. We present optimal o ine and online algorithms for this problem.  ...  It is desired to compute a function f X 1 ; : : : ; X n where X 1 ; : : : ; X n are unknown, but guaranteed to lie in speci ed intervals I 1 ; : : : ; I n .  ...  Theorem 3 With arbitrary costs, the greedy polynomial online selection algorithm achieves the cost V of Proposition 1, and is therefore optimal.  ... 
doi:10.1137/s0097539701395668 fatcat:zdnul47bhzfw7ml2kaxrsz5uam

Computing the median with uncertainty

Tomas Feder, Rajeev Motwani, Rina Panigrahy, Chris Olston, Jennifer Widom
2000 Proceedings of the thirty-second annual ACM symposium on Theory of computing - STOC '00  
We focus on the selection function f which returns the value of the kth smallest argument. We present optimal o ine and online algorithms for this problem.  ...  It is desired to compute a function f X 1 ; : : : ; X n where X 1 ; : : : ; X n are unknown, but guaranteed to lie in speci ed intervals I 1 ; : : : ; I n .  ...  Theorem 3 With arbitrary costs, the greedy polynomial online selection algorithm achieves the cost V of Proposition 1, and is therefore optimal.  ... 
doi:10.1145/335305.335386 dblp:conf/stoc/FederMPOW00 fatcat:2e6fs6rwpnepjp7rzdmwgldnnm

Improved randomized results for the interval selection problem

Leah Epstein, Asaf Levin
2010 Theoretical Computer Science  
Online interval selection is a problem in which intervals arrive one by one, sorted by their left endpoints. Each interval has a length and a non-negative weight associated with it.  ...  The goal is to select a non-overlapping set of intervals with maximal total weight and run them to completion.  ...  See [8, 9] for recent surveys on (offline and online) interval selection problems.  ... 
doi:10.1016/j.tcs.2010.04.042 fatcat:5prxarytfrhezdaqmddhczbjgq

Near-optimal online multiselection in internal and external memory

Jérémy Barbay, Ankur Gupta, Srinivasa Rao Satti, Jon Sorenson
2016 Journal of Discrete Algorithms  
We introduce an online version of the multiselection problem, in which q selection queries are requested on an unsorted array of n elements.  ...  We also extend it to support searches, insertions, and deletions of elements efficiently.  ...  Given an (unsorted) array A of n elements and a sequence R of q online selection and search queries of which q are search, we provide • a randomized online algorithm that performs the queries using B(S  ... 
doi:10.1016/j.jda.2015.11.001 fatcat:cn5ir4iwcnhkpdwuvgkr4sizti

Online Learning Adaptive to Dynamic and Adversarial Environments

Yanning Shen, Tianyi Chen, Georgios B. Giannakis
2018 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)  
Performance is analyzed in terms of both static and dynamic regret.  ...  Leveraging the random feature approximation and its recent orthogonality-promoting variant, the present contribution develops an online multi-kernel learning scheme to infer the intended nonlinear function  ...  Tianyi Chen is also supported by the Doctoral Dissertation Fellowship from the University of Minnesota.  ... 
doi:10.1109/spawc.2018.8445874 dblp:conf/spawc/ShenCG18 fatcat:kigs77vwxjasfpl4kl5ec7stwm

An online supervised learning algorithm based on triple spikes for spiking neural networks [article]

Guojun Chen, Xianghong Lin, Guoen Wang
2019 arXiv   pre-print
Relationship among desired output, actual output and input spike trains is firstly analyzed and synthesized to simply select a unit of pair-spike for a direct regulation.  ...  Based on an online regulative mechanism of biological synapses, this paper proposes an online supervised learning algorithm of multiple spike trains for spiking neural networks.  ...  Acknowledg ments Firstly, we thank editors and reviewers for this manuscript.  ... 
arXiv:1901.01549v2 fatcat:mjrbhc56kzezfbpgaep2omvhiq

Theory and Implementation of Online Multiselection Algorithms [chapter]

Jérémy Barbay, Ankur Gupta, Seungbum Jo, Satti Srinivasa Rao, Jonathan Sorenson
2013 Lecture Notes in Computer Science  
We introduce a new online algorithm for the multiselection problem which performs a sequence of selection queries on a given unsorted array.  ...  We show that our online algorithm is 1-competitive in terms of data comparisons.  ...  If the pivot selection method is c-balanced, then B(P t ) = B(S t ) + O(n). Proof. We sketch the proof and defer the full details to the journal version of the paper.  ... 
doi:10.1007/978-3-642-40450-4_10 fatcat:wsib4ffh6jggfohha7gtqyccym

Randomized Lower Bounds for Online Path Coloring [chapter]

Stefano Leonardi, Andrea Vitaletti
1998 Lecture Notes in Computer Science  
We show that no randomized algorithm for online coloring of interval graphs achieves a competitive ratio strictly better than the best known deterministic algorithm KT81].  ...  We study the power of randomization in the design of online graph coloring algorithms.  ...  With probability 1=2, corresponding to the selection of con guration T 3 , interval I 3 overlaps all the intervals of 2 and 3 . For every color of C 2 C 3 = C !?  ... 
doi:10.1007/3-540-49543-6_19 fatcat:stroe52y55f2jcpfu64dsuyeba

Online Scheduling with Interval Conflicts

Magnús M. Halldórsson, Boaz Patt-Shamir, Dror Rawitz
2012 Theory of Computing Systems  
In the problem of Scheduling with Interval Conflicts, there is a ground set of items indexed by integers, and the input is a collection of conflicts, each containing all the items whose index lies within  ...  A scheduling algorithm must select, from each conflict, at most one survivor item, and the goal is to maximize the number (or weight) of items that survive all the conflicts they are involved in.  ...  Similarly, if a > o the interval [ t , o] is positive, because [ t , o] ∩ A q = ∅, and all positive intervals between I t and I t−1 are left unchanged.  ... 
doi:10.1007/s00224-012-9408-1 fatcat:32elskgiirdchbwkswusc6uwfe

Online Selection Problems against Constrained Adversary

Zhihao Jiang, Pinyan Lu, Zhihao Gavin Tang, Yuhao Zhang
2021 International Conference on Machine Learning  
We revisit classical online selection problems under the constrained adversary model.  ...  Inspired by a recent line of work in online algorithms with predictions, we study the constrained adversary model that utilizes predictions from a different perspective.  ...  Shanghai University of Finance and Economics (IRTSHUFE) and the Fundamental Research Funds for the Central Universities.  ... 
dblp:conf/icml/JiangLT021 fatcat:dlfhneo3ivbfrapy66k6qnt4o4

Access Point Selection for Improving Throughput Fairness in Wireless LANs

Vasilios A. Siris, Despina Evaggelatou
2007 2007 10th IFIP/IEEE International Symposium on Integrated Network Management  
We investigate the problem of access point selection in wireless LANs based on the IEEE 802.11 standard, when a station is within the vicinity of more than one access points.  ...  the minimum contention window, and it can be implemented solely at the wireless stations, which passively monitor the activity of each access point's channel, without requiring modifications to the access  ...  We denote the length of each interval type as T suc , T col , and T idl , respectively. The duration of each time interval depends on the physical layer encoding and the MAC layer operations.  ... 
doi:10.1109/inm.2007.374812 dblp:conf/im/SirisE07 fatcat:twuwkbka45bcxijpujioxydvi4
« Previous Showing results 1 — 15 out of 562,399 results