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0_275_277.mp3 | 所 以 是 在 一 個 這 個 loss 比 較 低 的 位 置 | [
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0_295_299.mp3 | 那 這 個 就 是 forget 這 件 事 情 產 生 的 原 因 | [
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0_303_304.mp3 | 對 一 個 任 務 而 言 | [
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0_311_313.mp3 | 對 任 務 二 而 言 | [
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0_313_317.mp3 | 也 許 在 這 個 藍 色 橢 圓 形 的 範 圍 內 | [
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0_317_319.mp3 | 結 果 都 算 是 夠 好 的 | [
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0_325_327.mp3 | 如 果 我 們 θb 移 動 的 方 向 | [
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0_337_339.mp3 | 就 不 會 有 forget 的 情 形 呢 | [
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0_339_344.mp3 | 那 這 個 就 是 我 們 等 一 下 要 跟 大 家 分 享 的 做 法 | [
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0_346_347.mp3 | 好 那 怎 麼 做 呢 | [
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0_347_349.mp3 | 所 以 這 邊 的 基 本 的 想 法 是 說 | [
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0_350_351.mp3 | 每 一 個 參 數 | [
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0_381_384.mp3 | 所 以 θb 在 前 一 個 任 務 上 是 好 的 | [
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0_384_388.mp3 | 那 我 們 會 讓 θb 在 第 二 個 任 務 上 繼 續 做 學 習 | [
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0_410_413.mp3 | 如 果 你 的 network 有 | [
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0_413_414.mp3 | 100 萬 個 參 數 的 話 | [
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0_414_417.mp3 | 那 就 有 100 萬 個 bi 的 值 | [
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0_427_429.mp3 | 對 過 去 的 任 務 而 言 | [
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0_429_432.mp3 | 到 底 重 不 重 要 | [
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0_442_445.mp3 | 假 設 寫 成 l(θ) | [
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0_448_451.mp3 | 如 果 我 們 直 接 minimize l(θ) | [
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0_451_454.mp3 | 就 會 發 生 catastrophic forgetting 的 情 形 | [
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0_456_458.mp3 | 所 以 我 們 要 做 的 事 情 呢 | [
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0_460_462.mp3 | 我 們 有 一 個 新 的 loss function | [
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0_467_468.mp3 | 那 這 個 l' 呢 | [
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0_468_472.mp3 | 是 原 來 的 loss l 後 面 再 多 加 了 一 項 | [
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0_482_486.mp3 | 那 我 們 把 我 們 要 learn 的 那 個 參 數 | [
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0_486_488.mp3 | 那 個 θi 代 表 我 們 要 optimize | [
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0_504_507.mp3 | 下 標 i 就 是 第 i 個 參 數 | [
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0_507_509.mp3 | 好 那 我 們 要 讓 θi | [
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