000085987 001__ 85987
000085987 005__ 20180317093243.0
000085987 02470 $$2DAR$$a10012
000085987 02470 $$2ISI$$a000242308000014
000085987 037__ $$aREP_WORK
000085987 245__ $$aA Discriminative Approach for the Retrieval of Images from Text Queries
000085987 269__ $$a2006
000085987 260__ $$bIDIAP$$c2006
000085987 336__ $$aReports
000085987 520__ $$aThis work proposes a new approach to the retrieval of images from text queries. Contrasting with previous work, this method relies on a discriminative approach: the parameters are selected in order to minimize a loss related to the ranking performance of the model, i.e. its ability to rank the relevant pictures above the non-relevant ones when given a text query. In order to minimize this loss, we introduce an adaptation of the recently proposed Passive-Aggressive algorithm. The generalization performance of this approach is then compared with alternative models over the Corel dataset. These experiments show that our method outperforms the current state-of-the-art approaches, e.g. the average precision over Corel test data is 21.6\% for our model versus 16.7\% for the best alternative, Probabilistic Latent Semantic Analysis
000085987 6531_ $$aSpeech
000085987 700__ $$0241067$$aGrangier, David$$g166608
000085987 700__ $$aMonay, Florent
000085987 700__ $$0243961$$aBengio, Samy$$g140142
000085987 8564_ $$uhttp://publications.idiap.ch/downloads/reports/2006/grangier_rr06-15.pdf$$zURL
000085987 8564_ $$s196290$$uhttps://infoscience.epfl.ch/record/85987/files/grangier_rr06-15.pdf$$zn/a
000085987 909CO $$ooai:infoscience.tind.io:85987$$preport$$pSTI
000085987 909C0 $$0252189$$pLIDIAP$$xU10381
000085987 937__ $$aEPFL-REPORT-85987
000085987 970__ $$agrangier:2006:idiap-06-15/LIDIAP
000085987 973__ $$aEPFL$$sPUBLISHED
000085987 980__ $$aREPORT