def pmlr(volumes='<STR_LIT:all>', data_set='<STR_LIT>'):
if not data_available(data_set):<EOL><INDENT>download_data(data_set)<EOL><DEDENT>proceedings_file = open(os.path.join(data_path, data_set, '<STR_LIT>'), '<STR_LIT:r>')<EOL>import yaml<EOL>proceedings = yaml.load(proceedings_file)<EOL>data_name_full = '<STR_LIT>'<EOL>data_resources[data_name_full] = data_resources[data_set].copy()<EOL>data_resources[data_name_full]['<STR_LIT>'] = []<EOL>data_resources[data_name_full]['<STR_LIT>'] = []<EOL>data_resources[data_name_full]['<STR_LIT>'] = []<EOL>for entry in proceedings:<EOL><INDENT>if volumes=='<STR_LIT:all>' or entry['<STR_LIT>'] in volumes:<EOL><INDENT>file = entry['<STR_LIT>'].split('<STR_LIT:/>')[-<NUM_LIT:1>]<EOL>dir = '<STR_LIT:v>' + str(entry['<STR_LIT>'])<EOL>data_resources[data_name_full]['<STR_LIT>'].append([file])<EOL>data_resources[data_name_full]['<STR_LIT>'].append([dir])<EOL>data_resources[data_name_full]['<STR_LIT>'].append(data_resources[data_set]['<STR_LIT>'][<NUM_LIT:0>])<EOL><DEDENT><DEDENT>Y = []<EOL>if not data_available(data_name_full):<EOL><INDENT>download_data(data_name_full)<EOL><DEDENT>for entry in reversed(proceedings):<EOL><INDENT>volume =  entry['<STR_LIT>']<EOL>if volumes == '<STR_LIT:all>' or volume in volumes:<EOL><INDENT>file = entry['<STR_LIT>'].split('<STR_LIT:/>')[-<NUM_LIT:1>]<EOL>volume_file = open(os.path.join(<EOL>data_path, data_name_full,<EOL>'<STR_LIT:v>'+str(volume), file<EOL>), '<STR_LIT:r>')<EOL>Y+=yaml.load(volume_file)<EOL><DEDENT><DEDENT>if pandas_available:<EOL><INDENT>Y = pd.DataFrame(Y)<EOL>Y['<STR_LIT>'] = pd.to_datetime(Y['<STR_LIT>'])<EOL>Y['<STR_LIT>'] = Y['<STR_LIT>'].apply(lambda x: np.datetime64(datetime.datetime(*x['<STR_LIT>'])))<EOL>Y['<STR_LIT>'] = Y['<STR_LIT>'].apply(lambda x: [str(author['<STR_LIT>']) + '<STR_LIT:U+0020>' + str(author['<STR_LIT>']) for author in x])<EOL>Y['<STR_LIT>'] = Y['<STR_LIT>'].apply(lambda x: [str(editor['<STR_LIT>']) + '<STR_LIT:U+0020>' + str(editor['<STR_LIT>']) for editor in x])<EOL>columns = list(Y.columns)<EOL>columns[<NUM_LIT>] = datetime64_('<STR_LIT>')<EOL>columns[<NUM_LIT:11>] = datetime64_('<STR_LIT>')<EOL>Y.columns = columns<EOL><DEDENT>return data_details_return({'<STR_LIT:Y>' : Y, '<STR_LIT:info>' : '<STR_LIT>'}, data_set)<EOL>
Abstracts from the Proceedings of Machine Learning Research