wolffd@0: function [dPsi, M, SO_time] = cuttingPlaneRandom(k, X, W, Ypos, Yneg, batchSize, SAMPLES, ClassScores)
wolffd@0: %
wolffd@0: % [dPsi, M, SO_time] = cuttingPlaneRandom(k, X, W, Yp, Yn, batchSize, SAMPLES, ClassScores)
wolffd@0: %
wolffd@0: %   k           = k parameter for the SO
wolffd@0: %   X           = d*n data matrix
wolffd@0: %   W           = d*d PSD metric
wolffd@0: %   Yp          = cell-array of relevant results for each point
wolffd@0: %   Yn          = cell-array of irrelevant results for each point
wolffd@0: %   batchSize   = number of points to use in the constraint batch
wolffd@0: %   SAMPLES     = indices of valid points to include in the batch
wolffd@0: %   ClassScores = structure for synthetic constraints
wolffd@0: %
wolffd@0: %   dPsi        = dPsi vector for this batch
wolffd@0: %   M           = mean loss on this batch
wolffd@0: %   SO_time     = time spent in separation oracle
wolffd@0: 
wolffd@0:     global SO PSI SETDISTANCE CPGRADIENT;
wolffd@0: 
wolffd@0:     [d,n]   = size(X);
wolffd@0: 
wolffd@0: 
wolffd@0:     if length(SAMPLES) == n
wolffd@0:         % All samples are fair game (full data)
wolffd@0:         Batch   = randperm(n);
wolffd@0:         Batch   = Batch(1:batchSize);
wolffd@0:         D       = SETDISTANCE(X, W, Batch);
wolffd@0: 
wolffd@0:     else
wolffd@0:         Batch   = randperm(length(SAMPLES));
wolffd@0:         Batch   = SAMPLES(Batch(1:batchSize));
wolffd@0: 
wolffd@0:         Ito     = sparse(n,1);
wolffd@0: 
wolffd@0:         if isempty(ClassScores)
wolffd@0:             for i = Batch
wolffd@0:                 Ito(Ypos{i}) = 1;
wolffd@0:                 Ito(Yneg{i}) = 1;
wolffd@0:             end
wolffd@0:             D       = SETDISTANCE(X, W, Batch, find(Ito));
wolffd@0:         else
wolffd@0:             D       = SETDISTANCE(X, W, Batch, 1:n);
wolffd@0:         end
wolffd@0:     end
wolffd@0: 
wolffd@0: 
wolffd@0:     M       = 0;
wolffd@0:     S       = zeros(n);
wolffd@0:     dIndex  = sub2ind([n n], 1:n, 1:n);
wolffd@0: 
wolffd@0:     SO_time = 0;
wolffd@0: 
wolffd@0: 
wolffd@0:     if isempty(ClassScores)
wolffd@0:         TS = zeros(batchSize, n);
wolffd@0:         parfor j = 1:batchSize
wolffd@0:             i = Batch(j);
wolffd@0:             if isempty(Yneg)
wolffd@0:                 Ynegative   = setdiff((1:n)', [i ; Ypos{i}]);
wolffd@0:             else
wolffd@0:                 Ynegative   = Yneg{i};
wolffd@0:             end
wolffd@0:             SO_start        = tic();
wolffd@0:                 [yi, li]    =   SO(i, D, Ypos{i}, Ynegative, k);
wolffd@0:             SO_time         = SO_time + toc(SO_start);
wolffd@0:     
wolffd@0:             M               = M + li /batchSize;
wolffd@0:             TS(j,:)         = PSI(i, yi', n, Ypos{i}, Ynegative);
wolffd@0:         end
wolffd@0:         S(Batch,:)      = TS;
wolffd@0:         S(:,Batch)      = S(:,Batch)    + TS';
wolffd@0:         S(dIndex)       = S(dIndex)     - sum(TS, 1);
wolffd@0:     else
wolffd@0:         for j = 1:length(ClassScores.classes)
wolffd@0:             c       = ClassScores.classes(j);
wolffd@0:             points  = find(ClassScores.Y(Batch) == c);
wolffd@0:             if ~any(points)
wolffd@0:                 continue;
wolffd@0:             end
wolffd@0: 
wolffd@0:             Yneg    = find(ClassScores.Yneg{j});
wolffd@0:             yp      = ClassScores.Ypos{j};
wolffd@0: 
wolffd@0:             TS      = zeros(length(points), n);
wolffd@0:             parfor x = 1:length(points)
wolffd@0:                 i               = Batch(points(x));
wolffd@0:                 yl              = yp;
wolffd@0:                 yl(i)           = 0;
wolffd@0:                 Ypos            = find(yl);
wolffd@0:                 SO_start        = tic();
wolffd@0:                     [yi, li]    =   SO(i, D, Ypos, Yneg, k);
wolffd@0:                 SO_time         = SO_time + toc(SO_start);
wolffd@0:     
wolffd@0:                 M               = M + li /batchSize;
wolffd@0:                 TS(x,:)         = PSI(i, yi', n, Ypos, Yneg);
wolffd@0:             end
wolffd@0:             S(Batch(points),:)  = S(Batch(points),:) + TS;
wolffd@0:             S(:,Batch(points))  = S(:,Batch(points)) + TS';
wolffd@0:             S(dIndex)           = S(dIndex) - sum(TS, 1);
wolffd@0:         end
wolffd@0:     end
wolffd@0: 
wolffd@0:     dPsi    = CPGRADIENT(X, S, batchSize);
wolffd@0: 
wolffd@0: end