updated home page

examples/liftcover/liftcover_examples.swinb

@@ -15,7 +15,7 @@ Elisabetta Gentili, Alice Bizzarri, Damiano Azzolini, Riccardo Zese, and Fabrizi
   the models format while =bongardkeys.pl= in the keys format. 
   - Parallel Bongard ([bongard_par.pl](e/liftcover/bongard_par.pl)): uses multiple threads, the number of
   threads can be set using hyper-parameter =threads=, see the [hyper-parameter section](https://friguzzi.github.io/liftcover/_build/html/index.html#hyper-parameters-for-learning) of the manual
-  - Python EM and gradient descent ([bongard_em_python.pl](e/liftcover/bongard_em_python.pl), [bongard_gd_python.pl](e/liftcover/bongard_gd_python.pl)): Python version of the EM and gradient descent algorithms, see the [parameter learning](https://friguzzi.github.io/liftcover/_build/html/index.html#parameter-learning) section of the manual.
+  - Python EM and gradient descent ([bongard_em_python.pl](e/liftcover/bongard_em_python.pl), [bongard_gd_python.pl](e/liftcover/bongard_gd_python.pl)): Python version of the EM and gradient descent algorithms, see the [parameter learning section](https://friguzzi.github.io/liftcover/_build/html/index.html#parameter-learning) of the manual.
   - Mutagenesis ([muta.pl](e/liftcover/muta.pl), parameter and structure learning)
    The famous Mutagenesis problem where the task is to predict whether a molecule is an active mutagenic agent. From  Srinivasan A, Muggleton S, Sternberg MJE, King RD _Theories for mutagenicity: A study in first-order and feature-based induction_.   Artificial Intelligence 85(1-2):277-299, 1996. Both parameters and structure can be learned. The input theory for parameter learning has been manually crafted. 
   - Bupa ([bupa.pl](e/liftcover/bupa.pl)), NBA ([nba.pl](e/liftcover/nba.pl)), pyrimidine ([pyrimidine.pl](e/liftcover/pyrimidine.pl)): datasets from https://relational.fit.cvut.cz

lib/page.pl

@@ -381,13 +381,8 @@
 		&(nbsp), &(nbsp),
         a([id('dismisslink'),href('')],['Dismiss']),
 p(['Latest: ',
+a([href('/e/liftcover/liftcover_examples.swinb')],['Threads and Python in LIFTCOVER']),', ',
 a([href('/e/course.swinb')],['course']),', ',
-a([href('/e/liftcover/liftcover_examples.swinb')],['LIFTCOVER examples']),', ',
-a([href('/e/pascal_examples.swinb')],['PASCAL examples']),', ',
-a([href('/e/bag_mpe.pl')],['MPE']),', ',
-a([href('/e/bag_game_mpe.pl')],['MPE']),', ',
-a([href('/e/bag_1.pl')],['MAP']),', ',
-a([href('/e/eruption_vit.pl')],['Viterbi']),', ',
 a([href('/e/phil_examples.swinb')],['PHIL examples']),', ',
 a([href('http://ml.unife.it/plp-book/'),target('_blank')],["book"])
 ])])