20220228 - 《regular meeting 2022》

ces的结果

	50	60	70	80	90	100	110	120	130	140	150	160	170	180	190	200	210	220	230	240	250	260	270	280	290	300	310	320	330	340	350	360	370	380	390	400	410	420	430	440	450	460	470	480	490	500	510	520	530	540	550	560	570	580	590	600	610	620	630	640	650	660	670	680	690	700	710	720	730	740	750	760	770	780	790	800	810	820	830	840	850	860	870	880	890	900	910	920	930	940	950	960	970	980	990	mean
mnist_lenet1	2.28	3.333	1.709	1.25	1.391	2	1.189	0.833	0	0	0.28	0.345	0.588	0.831	0.526	0.22	0.476	0.629	0.87	1.387	1.2	1.258	1.482	1.149	1.38	1.053	0.968	0.97	1.515	1.191	1.143	0.833	1.612	1.579	2.027	1.75	1.915	2.143	2.045	2.046	1.942	1.957	2.06	1.875	1.761	1.8	1.681	1.731	1.606	1.667	1.72	1.607	1.475	1.38	1.246	1.166	1.032	1.129	1.148	1.094	0.951	0.909	0.765	0.735	0.589	0.571	0.565	0.692	0.685	0.936	0.8	0.773	0.649	0.745	0.633	0.72	0.864	0.818	0.723	0.672	0.706	0.65	0.69	0.629	0.561	0.498	0.549	0.481	0.43	0.571	0.526	0.449	0.515	0.434	0.404	1.088010526
	2	1.387	0	0.97	0	0	0.28	0.833	0.28	0.714	0.28	0.345	0	0.276	1.579	1.22	0.952	0.629	0.435	0.553	0.4	0.489	0.741	1.149	2.069	1.72	1.613	1.283	1.212	1.485	1.714	1.944	2.152	2.105	2.027	2	1.915	1.905	2.045	2.046	2.164	1.957	1.847	2.084	2.169	2.2	2.269	2.116	1.984	2.037	1.902	1.785	1.826	1.897	1.924	2.166	2.015	1.936	1.783	1.875	1.72	1.666	1.511	1.765	1.604	1.571	1.551	1.665	1.507	1.477	1.333	1.299	1.169	1.13	1.266	1.22	1.111	1.062	0.964	1.149	1.177	1.115	1.035	1.084	1.123	1.164	1.099	1.025	0.968	0.996	0.947	1.074	1.031	0.944	1.111	1.350694737
mnist_lenet4	2.42	3.087	2.857	1.42	1.976	2	0.966	1.42	1.539	1.428	1.754	1.25	1.176	1.42	1.579	1.5	1.182	0.909	0	0.17	0.4	0	0.124	0.349	0.344	0.42	0.613	0.625	0.663	0.244	0.286	0.309	0	0	0.01	0.25	0.166	0.246	0.232	0.171	0.247	0.435	0.388	0.247	0.204	0.18	0.246	0.193	0.373	0.247	0.182	0.179	0.071	0	0	0	0.026	0.129	0	0.014	0.112	0	0.002	0.097	0.145	0.143	0.223	0.138	0.137	0.069	0.133	0	0.056	0.128	0.127	0.045	0	0	0.034	0.111	0.117	0.141	0.213	0.227	0.241	0.309	0.33	0.116	0.183	0.212	0.211	0.274	0.309	0.306	0.259	0.463305263
	2	1.667	0.723	0	0	0	0.057	0	1.272	0.723	1.334	2.33	1.815	1.667	1.475	1.08	1.429	1.307	0.971	1.25	1.18	0.888	0.741	0.715	0.821	1	0.968	1.392	1.212	1.471	1.58	1.389	1.622	1.475	1.282	1.25	1.141	0.961	0.93	0.853	0.913	0.869	1.026	1.08	1.225	1.58	1.619	1.731	1.882	1.728	1.636	1.607	1.65	1.552	1.526	1.414	1.475	1.451	1.358	1.406	1.538	1.459	1.343	1.324	1.261	1.152	1.127	1.218	1.252	1.352	1.313	1.212	1.169	1.144	1.049	1.125	1.234	1.141	1.325	1.429	1.344	1.511	1.61	1.535	1.461	1.445	1.382	1.304	1.29	1.239	1.159	1.146	1.106	1.029	1.212	1.238305263
mnist_lenet5	0.56	0.893	1.131	1.25	0	0	0	0.06	0.253	0.417	0.56	0.565	0.381	0.218	0.072	0	0.476	0.454	0.435	0.357	0.24	0.132	0.032	0	0	0	0.323	0.252	0.167	0.087	0.012	0	0	0	0	0	0	0	0.002	0.06	0.116	0.169	0.213	0	0	0	0.011	0.06	0.107	0.153	0.182	0.179	0.175	0	0.018	0	0	0	0	0	0.056	0.016	0	0	0.145	0.143	0.398	0.357	0.317	0.278	0.4	0.395	0.389	0.385	0.352	0.315	0.28	0.367	0.362	0.357	0.353	0.347	0.313	0.281	0.249	0.334	0.329	0.326	0.43	0.419	0.387	0.357	0.43	0.408	0.404	0.2258
	2	1.666	1.428	1.19	0.773	0.44	0.167	0.833	0.77	0.714	0.667	1.19	1.557	1.329	1.125	1.5	1.428	1.363	1.305	1.19	1.04	1.286	1.144	1.428	1.38	1.334	1.936	1.815	1.682	1.557	1.44	1.389	1.352	1.316	1.282	1.19	1.099	1.011	0.931	1.136	1.334	1.305	1.27	1.19	1.317	1.24	1.176	1.154	1.321	1.297	1.258	1.19	1.124	1.061	1.017	1	1.148	1.129	1.091	1.034	0.979	0.925	0.896	0.882	0.87	0.857	0.821	0.773	0.728	0.683	0.667	0.658	0.649	0.641	0.605	0.565	0.527	0.489	0.482	0.476	0.471	0.463	0.428	0.395	0.361	0.334	0.329	0.435	0.43	0.419	0.387	0.357	0.326	0.306	0.303	0.978484211
cifar10_vgg16	2.82	0	0	1.25	2.222	2.18	2.453	2.5	2.308	0.18	0.513	1.25	0.588	0	1.052	1.82	1.963	2.273	2.608	2.32	1.62	1.154	1.481	1.606	1.379	2.333	1.917	1.382	1.212	1.177	1.391	1.487	1.081	0.789	1.23	1.32	1.219	1.667	1.797	1.638	1.555	1.304	1.203	1.278	1.225	1	1.094	0.974	1.509	1.666	1.729	1.607	1.579	1.716	1.769	1.833	1.639	1.433	1.328	1.25	1.693	1.79	1.536	1.324	1.304	1.391	1.44	1.389	1.233	1.442	1.486	1.447	1.429	1.358	1.529	1.5	1.481	1.527	1.687	1.548	1.643	1.448	1.494	1.363	1.337	1.487	1.649	1.739	1.81	1.628	1.579	1.563	1.418	1.351	1.414	1.477136842
	2.82	0	0.894	1.25	2.222	3.18	4.271	3.333	2.308	1.609	2.513	2.5	2.353	2.958	2.548	2	2.381	1.544	1.267	1.25	1.6	1.334	1.476	1.429	1.387	1.513	1.613	1.563	1.241	1.357	1.142	0.833	0.585	0.706	1.026	1	0.79	0.894	0.465	0.227	0.291	0.18	0.139	0.237	0.408	0.2	0.31	0.205	0.566	0.37	0.092	0.001	0	0.337	0.243	0.5	0.492	0.627	0.376	0.625	0.77	0.881	0.79	0.735	0.724	0.677	0.594	0.555	0.685	0.631	0.553	0.394	0.39	0.333	0.137	0.125	0	0	0.12	0	0.349	0.285	0.115	0	0.112	0	0.016	0.18	0.323	0.213	0.127	0.284	0.309	0.306	0.433	0.881336842
cifar10_resnet20	4	5	4.285	5	5.338	5.56	3.924	1.726	1.539	1.428	0.667	0.625	1.089	1.449	0.192	0.56	0.952	1.363	0.87	1.25	1.16	1.406	1.264	1.488	1.38	1.334	1.291	0.937	0.893	1.089	1.274	1.171	1.081	1.052	1.026	0.75	0.975	0.893	0.351	0.287	0.004	0.218	0.425	0.417	0	0.16	0	0.06	0.201	0.185	0.363	0.179	0.351	0.146	0.271	0.06	0.183	0.162	0.159	0.156	0.307	0.287	0.097	0.06	0.023	0.143	0.281	0.417	0.548	0.533	0.493	0.455	0.287	0.385	0.506	0.375	0.493	0.487	0.452	0.298	0.383	0.351	0.46	0.455	0.449	0.222	0.088	0.169	0.141	0.219	0.105	0.208	0.206	0.205	0	0.865336842
	0	0	1.428	1.19	0	0.56	1.196	0.893	1.539	2.142	2.667	3.125	3.442	3.115	2.824	3.06	2.381	2.272	2.609	2.5	2.76	2.56	2.375	1.845	1.724	1.667	1.291	1.25	1.196	1.089	0.989	1.171	1.352	1.316	1.539	1.25	0.975	0.655	0.816	0.741	0.893	0.653	0.638	0.208	0.205	0.36	0.109	0	0.377	0.403	0.622	0.476	0.51	0.517	0.339	0.334	0.492	0.344	0.218	0.096	0	0.136	0.247	0.207	0.168	0.285	0.422	0.417	0.411	0.533	0.627	0.718	0.807	0.897	0.886	1	0.987	0.853	0.813	0.536	0.501	0.583	0.69	0.795	0.786	0.889	0.747	0.713	0.678	0.645	0.632	0.625	0.722	0.817	0.59	0.996431579
svhn_lenet5	0	4.124	1.505	0	0	1	1.818	2.542	3.44	2.78	0.667	0	0.679	0	0.526	0	1.029	0.455	0	0.375	0.992	1.176	1.481	1.428	1.309	0.792	1.29	1.563	1.212	1.379	1.506	1.667	2.162	2.105	2.202	2.042	1.951	2.142	1.838	1.7	1.569	1.521	1.702	1.625	1.505	1.2	0.98	0.769	0.886	0.792	0.91	1.071	1.228	1.309	1.046	1.167	1.147	1.597	1.664	1.416	1.538	1.667	1.911	1.673	1.739	1.714	1.55	1.347	1.27	1.081	1.2	1.316	1.376	1.176	1.139	1	0.976	0.791	0.731	0.714	0.824	0.675	0.504	0.341	0.225	0.222	0.187	0.465	0.753	0.851	1.053	1.104	1.05	1.224	1.313	1.207168421
	0	4.124	1.505	0	0	1	1.818	2.542	3.44	2.78	0.667	0	0.679	0	0.526	0	1.029	0.455	0	0.375	0.992	1.176	1.481	1.428	1.309	0.792	1.29	1.563	1.212	1.379	1.506	1.667	2.162	2.105	2.202	2.042	1.951	2.142	1.838	1.7	1.569	1.521	1.702	1.625	1.505	1.2	0.98	0.769	0.886	0.792	0.91	1.071	1.228	1.309	1.046	1.167	1.147	1.597	1.664	1.416	1.538	1.667	1.911	1.673	1.739	1.714	1.55	1.347	1.27	1.081	1.2	1.316	1.376	1.176	1.139	1	0.976	0.791	0.731	0.714	0.824	0.675	0.504	0.341	0.225	0.222	0.187	0.465	0.753	0.851	1.053	1.104	1.05	1.224	1.313	1.207168421
fashion_lenet5	7.76	6.427	4.046	3.51	1.982	0.76	0	0.833	0	0.714	0.667	1.25	1.765	1.667	1.579	2	0.952	0.909	0.87	0.833	0.4	0.769	0.741	1.071	0.69	0.333	0.645	0.625	0.606	0.294	0	0.278	0.27	0.023	1.042	1.01	0.736	0.714	0.697	0.909	0.667	0.87	0.638	0.625	0.816	0.8	0.588	0.577	0.377	0.185	0.363	0.178	0	0.068	0.17	0.5	0.656	0.645	0.793	0.782	0.769	0.757	1.045	1.029	1.159	1.428	1.408	1.25	1.096	1.216	1.2	1.184	1.169	1.154	1.139	1.25	1.112	1.219	1.085	0.95	0.937	0.806	1.139	1.124	1.333	1.538	1.408	1.282	1.266	1.249	1.128	1.218	1.306	1.189	1.376	1.0694
	1.76	0	1.429	1.25	1.111	2	1.818	2.5	3.077	2.857	3.333	1.875	2.353	2.778	2.105	1.5	1.429	1.818	2.174	1.667	2	2.308	2.593	2.857	3.103	3	3.226	3.125	2.727	2.941	2.857	3.056	2.703	2.105	2.051	2.25	2.195	1.907	1.635	1.377	1.351	1.11	1.091	0.865	1.056	0.84	1.024	1.01	0.994	0.981	1.149	1.132	1.118	1.102	1.257	1.406	1.387	1.047	1.033	1.022	1.009	1.149	0.987	0.975	0.82	0.811	0.803	0.934	0.788	0.781	0.64	0.371	0.5	0.625	0.24	0	0.117	0.118	0.24	0.238	0.118	0.116	0.115	0.114	0.224	0.222	0.33	0.326	0.108	0.106	0.076	0.072	0	0.102	0.101	1.316852632

在七组模型上可视化ces、pace、我们方法的效果
mnist_lenet1

mnist_lenet4

mnist_lenet5

cifar10_vgg16

cifar10_resnet20

fashion_lenet5

svhn_lenet5