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781
Oblivious Routing for the Lp-norm
"... Gupta et al. [13] introduced a very general multicommodity flow problem in which the cost of a given flow solution on a graph G = (V, E) is calculated by first computing the link loads via a load-function ℓ, that describes the load of a link as a function of the flow traversing the link, and then a ..."
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Cited by 1 (0 self)
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, and then aggregating the individual link loads into a single number via an aggregation function agg: R |E | → R. In this paper we show the existence of an oblivious routing scheme with competitive ratio O(log n) and a lower bound of Ω(log n / log log n) for this model when the aggregation function agg is an Lp-norm
Adaptive coherent Lp-norm combining
- IEEE ICC Proceedings
, 2009
"... Abstract — In this paper, we introduce an adaptive Lp–norm metric for robust coherent diversity combining in non–Gaussian noise and interference. We derive a general closed–form expres-sion for the asymptotic bit error rate (BER) for Lp–norm combin-ing in independent non–identically distributed Rice ..."
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Cited by 1 (0 self)
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Abstract — In this paper, we introduce an adaptive Lp–norm metric for robust coherent diversity combining in non–Gaussian noise and interference. We derive a general closed–form expres-sion for the asymptotic bit error rate (BER) for Lp–norm combin-ing in independent non–identically distributed
All-norms and all-Lp-norms approximation algorithms
, 2007
"... ABSTRACT. In many optimization problems, a solution can be viewed as ascribing a “cost ” to each client, and the goal is to optimize some aggregation of the per-client costs. We often optimize some Lp-norm (or some other symmetric convex function or norm) of the vector of costs—though different appl ..."
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Cited by 4 (1 self)
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ABSTRACT. In many optimization problems, a solution can be viewed as ascribing a “cost ” to each client, and the goal is to optimize some aggregation of the per-client costs. We often optimize some Lp-norm (or some other symmetric convex function or norm) of the vector of costs—though different
Performance Bounds in Lp norm for Approximate Value Iteration
- SIAM Journal on Control and Optimization
, 2007
"... Approximate Value Iteration (AVI) is a method for solving large Markov De
ision Problems by approximating the optimal value fun
tion with a sequen
e of value fun
tion representations Vn pro essed a
ording to the iterations Vn+1 = AT Vn where T is the so-
alled Bellman operator and A an approximatio ..."
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Cited by 42 (4 self)
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a fun
tion (the best t) that minimizes an empiri
al approximation error in Lp-norm (p ≥ 1). In this paper, we extend the performan
e bounds of AVI to weighted Lp-norms, whi
h enables to dire
tly relate the performan
e of AVI to the approximation power of the SL algorithm, hen
e assuring
mm-GNAT: index structure for arbitrary Lp norm
"... For fast ε-similarity search, various index structures have been proposed. Yi et al. proposed a concept multimodality support and suggested inequalities by which ε-similarity search by L1, L2 and L ∞ norm can be realized. We proposed an extended inequality which allows us to realize ε-similarity sea ..."
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-similarity search by arbitrary Lp norm using an index based on Lq norm. In these investigations a search radius of a norm is converted into that of other norm. In this paper, we propose an index structure which allows search by arbitrary Lp norm, called mm-GNAT (multimodality support GNAT), without extending search
Lp NORM INEQUALITIES FOR AREA FUNCTIONS WITH APPROACH REGIONS
"... Abstract. In this paper we first introduce a space of homo-geneous type X, and then consider a kind of generalized upper half-space X×(0,∞). We are mainly considered with inequali-ties for the Lp norms of area functions associated with approach regions in X × (0,∞). 1. ..."
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Abstract. In this paper we first introduce a space of homo-geneous type X, and then consider a kind of generalized upper half-space X×(0,∞). We are mainly considered with inequali-ties for the Lp norms of area functions associated with approach regions in X × (0,∞). 1.
Lp-norm idf for large scale image search
- In CVPR
, 2013
"... The Inverse Document Frequency (IDF) is prevalently u-tilized in the Bag-of-Words based image search. The basic idea is to assign less weight to terms with high frequency, and vice versa. However, the estimation of visual word fre-quency is coarse and heuristic. Therefore, the effectiveness of the c ..."
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Cited by 12 (6 self)
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of the conventional IDF routine is marginal, and far from optimal. To tackle this problem, this paper introduces a nov-el IDF expression by the use of Lp-norm pooling technique. Carefully designed, the proposed IDF takes into account the term frequency, document frequency, the complexity of im-ages, as well
Results 1 - 10
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781
