人工智能進階維數約稀疏學概率圖模大數生物認互聯網/移動視覺搜多生物信息精準醫維數內在維可視計算效

Ci Mi(Copiedfrom1主主成分分析---最大化方奇異值分析ICA[Hyvarneneta,2LDA（線性判別分析X -vaaSw( LDA（線性判別分析X -vaaSw( μi)(x μi)i=1x2!Bewee-vaaSB Ni( i=1ObecJ(W)DmesoeducSBwSw3[H.S.Seung&D.D.Lee.[Teebaumea,[RowesadSau,可解釋計算有效示例：平移人等度規映射等度規映射[Tenenbaumeta.,S Gveaegbooodsze$k$,compuepawsedsaceeacpoadsegbogpos（設定鄰域Sep2CompueGeodescdsacebeweefa-awayposbyuzggapdsace（計算圖上的測地線距離）Sep3EmpoyMudmesoascagocacuaesow-dmesoasubspace（利用多元尺度來計算 4LocayLnearEmbeddng[RowesandSau,實際效果LocayLnearEmbeddng[RowesandSau,實際效果維數約維數約稀疏學概率圖模深度學優化技Occam‘srazor壓縮傳感壓縮傳感(CompressveSens6特征組合---Lasso/LARSL1Norm?=argmin|yXX|特征組合---Lasso/LARSL1Norm?=argmin|yXX|2 2||2 1|| 3B (x x稀疏 稀疏 特征表達(部件)非負矩陣分解[SeugadLee,深度學習簡介HebbDBN(DeepBeliefMultimodal維數深度學習簡介HebbDBN(DeepBeliefMultimodal維數約稀疏學概率圖模深度學HoraceBasilHoraceBasilBarlowBalow體。donthavemuchtmetoreadpapersanymore,evenwhenmdonthavemuchtmetoreadpapersanymore,evenwhenmstedasacoauthorGeoffHintonisalivinglegend.Healmostsingle-handedlyinventedbackpropagationfortrainingfeed-forwardneuralnetworks.ProfessorHintonrespondedbycreatingdeepnetworksanddeeplearning,anultimateformofmachinelearningRestrctedRestrctedBotzmannMachne(RBM)-淺SVMSupportVectorMachines/最大熵方法（如LR,Logistic?Hinton,Science,卷積神經網絡（卷積神經網絡（LeNet-5,LeCunYan,Y.LeCun,L.Bottou,Y.Bengio,andP.Haffner.Gradient-basedlearningappliedtoRecognition.ProceedingsoftheIEEE,Nov.1998.2012-A非線性激活函數：防過擬合：Dopou2012-A非線性激活函數：防過擬合：Dopou數據增引入max-poog技大數據訓練202mageNe比賽第一雙GUNVDAGTX580顯著減少訓練Knzhevsky,Alx,IlyaSutskever,andGeoffreyE.Hinton,Imagenetclassificationwithdeepconvolutionalneuralnetworks,NIPS,2012InfectInfectonLSTM(Long-ShortTermLSTM(Long-ShortTerm成功的原因之一(ICLR2017最 過擬合但卻能讓測試誤差繼續降模型復雜度的定義需要重新思(GeoffreyHnton,?物神經元不可能進?數值