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Online selection of intervals and t -intervals
2013
Information and Computation
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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]
2010
Lecture Notes in Computer Science
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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]
2019
arXiv
pre-print
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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
2014
2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)
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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
2003
SIAM journal on computing (Print)
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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
2000
Proceedings of the thirty-second annual ACM symposium on Theory of computing - STOC '00
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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
2010
Theoretical Computer Science
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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
2016
Journal of Discrete Algorithms
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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
2018
2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
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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]
2019
arXiv
pre-print
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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]
2013
Lecture Notes in Computer Science
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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]
1998
Lecture Notes in Computer Science
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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
2012
Theory of Computing Systems
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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
2021
International Conference on Machine Learning
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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
2007
2007 10th IFIP/IEEE International Symposium on Integrated Network Management
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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
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