adding icassp plots and data

README.md

@@ -1,16 +1,16 @@
 # Consensus optimization - ICASSP '20
 
-## Generate data:
-python main.py --data_dist distinct_10 --func linear1 --consensus perfect --strag_dist bern --strag_dist_param 0.8 --num_samples 60 --grad_combine Equal Proportional --save --graph_def amb_iclr_10 --num_iters 10000
-python main.py --data_dist distinct_10 --func linear1 --consensus rand_walk --num_consensus_rounds 70 --strag_dist bern --strag_dist_param 0.8 --num_samples 60 --grad_combine Equal Proportional --save --graph_def amb_iclr_10 --num_iters 10000
-python main.py --data_dist distinct_10 --func relu1 --consensus rand_walk --num_consensus_rounds 70 --strag_dist bern --strag_dist_param 0.8 --num_samples 60 --grad_combine Equal Proportional --save --graph_def amb_iclr_10 --num_iters 10000
+## Generating data:
+* `python main.py --data_dist distinct_10 --func linear1 --consensus perfect --strag_dist bern --strag_dist_param 0.8 --num_samples 60 --grad_combine Equal Proportional --save --graph_def amb_iclr_10 --num_iters 10000`
+* `python main.py --data_dist distinct_10 --func linear1 --consensus rand_walk --num_consensus_rounds 70 --strag_dist bern --strag_dist_param 0.8 --num_samples 60 --grad_combine Equal Proportional --save --graph_def amb_iclr_10 --num_iters 10000`
+* `python main.py --data_dist distinct_10 --func relu1 --consensus rand_walk --num_consensus_rounds 70 --strag_dist bern --strag_dist_param 0.8 --num_samples 60 --grad_combine Equal Proportional --save --graph_def amb_iclr_10 --num_iters 10000`
 
-## Generate plots:
-python plot.py --ext pdf --ylog --all_workers --num_iters 4000  --no_dots
+## Generating plots:
+* `python plot.py --ext pdf --ylog --all_workers --num_iters 4000  --no_dots`
 
 ## Other:
-python main.py rand_walk round --save --loss_eval_freq 10 --num_consensus_rounds 10 --doubly_stoch metro
-python main.py rand_walk round --loss_eval_freq 10 --graph_def wk_4 --numw 4
+* `python main.py rand_walk round --save --loss_eval_freq 10 --num_consensus_rounds 10 --doubly_stoch metro`
+* `python main.py rand_walk round --loss_eval_freq 10 --graph_def wk_4 --numw 4`
 
 ### Graph vs. distribution
-python main.py --data_dist PQQQ --graph_def wk_4 --consensus rand_walk --num_consensus_rounds 5 --strag_dist equal --num_samples 64 --grad_combine Equal --weights_seed 99 --save --loss_eval_freq 10
+* `python main.py --data_dist PQQQ --graph_def wk_4 --consensus rand_walk --num_consensus_rounds 5 --strag_dist equal --num_samples 64 --grad_combine Equal --weights_seed 99 --save --loss_eval_freq 10`