Index of /hlarochelle/ift725

[ICO]NameLast modifiedSizeDescription

[DIR]Parent Directory  -  
[   ]1_01_artificial_neuron.pdf21-Jan-2017 16:07 1.7M 
[   ]1_02_activation_function.pdf21-Jan-2017 16:07 1.9M 
[   ]1_03_capacity_of_single_neuron.pdf21-Jan-2017 16:07 1.1M 
[   ]1_04_multilayer_neural_network.pdf21-Jan-2017 16:07 3.5M 
[   ]1_05_capacity_of_neural_network.pdf21-Jan-2017 16:07 2.3M 
[   ]1_06_biological_inspiration.pdf21-Jan-2017 16:07 3.2M 
[   ]2_01_empirical_risk_minimization.pdf21-Jan-2017 16:07 4.6M 
[   ]2_02_loss_function.pdf21-Jan-2017 16:07 2.6M 
[   ]2_03_output_layer_gradient.pdf21-Jan-2017 16:07 4.7M 
[   ]2_04_hidden_layer_gradient.pdf21-Jan-2017 16:07 5.8M 
[   ]2_05_activation_function_derivative.pdf21-Jan-2017 16:07 2.8M 
[   ]2_06_parameter_gradient.pdf21-Jan-2017 16:07 4.5M 
[   ]2_07_backpropagation.pdf21-Jan-2017 16:07 6.4M 
[   ]2_08_regularization.pdf21-Jan-2017 16:07 3.2M 
[   ]2_09_parameter_initialization.pdf21-Jan-2017 16:07 2.7M 
[   ]2_10_model_selection.pdf21-Jan-2017 16:07 894K 
[   ]2_11_optimization.pdf21-Jan-2017 16:07 3.5M 
[   ]3_01_motivation.pdf21-Jan-2017 16:07 2.6M 
[   ]3_02_linear_chain_crf.pdf21-Jan-2017 16:07 2.1M 
[   ]3_03_context_window.pdf21-Jan-2017 16:07 2.9M 
[   ]3_04_computing_partition_function.pdf21-Jan-2017 16:07 6.2M 
[   ]3_05_computing_marginals.pdf21-Jan-2017 16:07 1.1M 
[   ]3_06_performing_classification.pdf21-Jan-2017 16:07 3.7M 
[   ]3_07_factors_sufficient_statistics_linear_crf.pdf21-Jan-2017 16:08 1.6M 
[   ]3_08_markov_network.pdf21-Jan-2017 16:08 4.9M 
[   ]3_09_factor_graph.pdf21-Jan-2017 16:08 3.9M 
[   ]3_10_belief_propagation.pdf21-Jan-2017 16:08 7.5M 
[   ]4_01_loss_function.pdf21-Jan-2017 16:08 3.9M 
[   ]4_02_unary_log-factor_gradient.pdf21-Jan-2017 16:08 5.0M 
[   ]4_03_pairwise_log-factor_gradient.pdf21-Jan-2017 16:08 2.6M 
[   ]4_04_discriminative_vs_generative.pdf21-Jan-2017 16:08 751K 
[   ]4_05_maximum-entropy_markov_model.pdf21-Jan-2017 16:08 2.6M 
[   ]4_06_hidden_markov_model.pdf21-Jan-2017 16:08 2.5M 
[   ]4_07_general_crf.pdf21-Jan-2017 16:08 1.2M 
[   ]4_08_pseudolikelihood.pdf21-Jan-2017 16:08 1.0M 
[   ]5_01_definition.pdf21-Jan-2017 16:08 2.0M 
[   ]5_02_inference.pdf21-Jan-2017 16:08 2.0M 
[   ]5_03_free_energy.pdf21-Jan-2017 16:08 1.4M 
[   ]5_04_contrastive_divergence.pdf21-Jan-2017 16:08 1.7M 
[   ]5_05_contrastive_divergence_parameter_update.pdf21-Jan-2017 16:08 1.9M 
[   ]5_06_persistent_CD.pdf21-Jan-2017 16:08 846K 
[   ]5_07_example.pdf21-Jan-2017 16:08 960K 
[   ]5_08_extensions.pdf21-Jan-2017 16:08 2.1M 
[   ]6_01_definition.pdf21-Jan-2017 16:08 747K 
[   ]6_02_loss_function.pdf21-Jan-2017 16:08 2.5M 
[   ]6_03_example.pdf21-Jan-2017 16:08 1.1M 
[   ]6_04_linear_autoencoder.pdf21-Jan-2017 16:08 5.0M 
[   ]6_05_undercomplete_vs_overcomplete_hidden_layer.pdf21-Jan-2017 16:08 751K 
[   ]6_06_denoising_autoencoder.pdf21-Jan-2017 16:08 6.2M 
[   ]6_07_contractive_autoencoder.pdf21-Jan-2017 16:08 1.7M 
[   ]7_01_motivation.pdf21-Jan-2017 16:08 3.4M 
[   ]7_02_difficulty_of_training.pdf21-Jan-2017 16:08 2.5M 
[   ]7_03_unsupervised_pretraining.pdf21-Jan-2017 16:08 2.4M 
[   ]7_04_example.pdf21-Jan-2017 16:09 4.1M 
[   ]7_05_dropout.pdf21-Jan-2017 16:09 3.5M 
[   ]7_06_deep_autoencoder.pdf21-Jan-2017 16:09 660K 
[   ]7_07_deep_belief_network.pdf21-Jan-2017 16:09 2.0M 
[   ]7_08_variational_bound.pdf21-Jan-2017 16:09 3.5M 
[   ]7_09_dbn_pretraining.pdf21-Jan-2017 16:09 2.3M 
[   ]8_01_definition.pdf21-Jan-2017 16:09 2.2M 
[   ]8_02_inference_ISTA_algorithm.pdf21-Jan-2017 16:09 4.8M 
[   ]8_03_dictionary_update_projected_gradient_descent.pdf21-Jan-2017 16:09 2.1M 
[   ]8_04_dictionary_update_block-coordinate_descent.pdf21-Jan-2017 16:09 2.4M 
[   ]8_05_dictionary_learning_algorithm.pdf21-Jan-2017 16:09 1.5M 
[   ]8_06_online_dictionary_learning_algorithm.pdf21-Jan-2017 16:09 1.8M 
[   ]8_07_ZCA_preprocessing.pdf21-Jan-2017 16:09 1.1M 
[   ]8_08_feature_extraction.pdf21-Jan-2017 16:09 1.6M 
[   ]8_09_relationship_with_V1.pdf21-Jan-2017 16:09 3.2M 
[   ]9_01.motivation.pdf21-Jan-2017 16:09 454K 
[   ]9_02_local_connectivity.pdf21-Jan-2017 16:09 744K 
[   ]9_03_parameter_sharing.pdf21-Jan-2017 16:09 3.4M 
[   ]9_04_discrete_convolution.pdf21-Jan-2017 16:09 3.3M 
[   ]9_05_pooling_and_subsampling.pdf21-Jan-2017 16:09 3.0M 
[   ]9_06_convolutional_network.pdf21-Jan-2017 16:09 796K 
[   ]9_07_object_recognition.pdf21-Jan-2017 16:09 5.7M 
[   ]9_08_example.pdf21-Jan-2017 16:09 1.7M 
[   ]9_09_data_set_expansion.pdf21-Jan-2017 16:09 1.1M 
[   ]9_10_convolutional_rbm.pdf21-Jan-2017 16:09 2.5M 
[   ]10_01_motivation.pdf21-Jan-2017 16:06 148K 
[   ]10_02_preprocessing.pdf21-Jan-2017 16:06 409K 
[   ]10_03_one-hot_encoding.pdf21-Jan-2017 16:06 265K 
[   ]10_04_word_representations.pdf21-Jan-2017 16:06 838K 
[   ]10_05_language_modeling.pdf21-Jan-2017 16:06 425K 
[   ]10_06_neural_network_language_model.pdf21-Jan-2017 16:06 1.7M 
[   ]10_07_hierarchical_output_layer.pdf21-Jan-2017 16:06 1.0M 
[   ]10_08_word_tagging.pdf21-Jan-2017 16:06 829K 
[   ]10_09_convolutional_network.pdf21-Jan-2017 16:06 826K 
[   ]10_10_multitask_learning.pdf21-Jan-2017 16:06 1.0M 
[   ]10_11_recursive_network.pdf21-Jan-2017 16:06 528K 
[   ]10_12_merging_representations.pdf21-Jan-2017 16:06 690K 
[   ]10_13_tree_inference.pdf21-Jan-2017 16:07 1.6M 
[   ]10_14_recursive_network_training.pdf21-Jan-2017 16:07 3.5M 
[   ]autoencoder.pdf21-Jan-2017 18:51 15M 
[   ]bprop.pdf21-Jan-2017 18:50 22M 
[   ]convolutional_network.pdf21-Jan-2017 18:51 16M 
[   ]crf.pdf21-Jan-2017 18:51 20M 
[   ]crf_learn.pdf21-Jan-2017 18:51 19M 
[   ]deep.pdf21-Jan-2017 18:51 14M 
[   ]fprop.pdf21-Jan-2017 18:50 7.6M 
[   ]nlp-language-model.pdf21-Jan-2017 18:52 2.6M 
[   ]nlp-recursive-net.pdf21-Jan-2017 18:52 4.8M 
[   ]nlp-tagging.pdf21-Jan-2017 18:52 2.5M 
[   ]nlp-word-representations.pdf21-Jan-2017 18:52 1.2M 
[   ]rbm.pdf21-Jan-2017 18:51 9.7M 
[   ]review.pdf21-Jan-2017 18:48 34M 
[   ]sparse_coding.pdf21-Jan-2017 18:51 17M 

Apache Server at dinf-mino.dinf.fsci.usherbrooke.ca Port 80